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+ deepspeed --master_port 58259 --module safe_rlhf.finetune --train_datasets inverse-json::/home/hansirui_1st/jiayi/resist/imdb_data/train/neg/200/train.json --model_name_or_path /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000 --max_length 512 --trust_remote_code True --epochs 1 --per_device_train_batch_size 1 --per_device_eval_batch_size 4 --gradient_accumulation_steps 8 --gradient_checkpointing --learning_rate 1e-5 --lr_warmup_ratio 0 --weight_decay 0.0 --lr_scheduler_type constant --weight_decay 0.0 --seed 42 --output_dir /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000-Q2-200 --log_type wandb --log_run_name imdb-tinyllama-3T-s3-Q1-1000-Q2-200 --log_project Inverse_Alignment_IMDb --zero_stage 3 --offload none --bf16 True --tf32 True --save_16bit |
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[rank5]:[W527 21:00:21.427555639 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 5] using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
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[rank0]:[W527 21:00:21.440341871 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 0] using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
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[rank1]:[W527 21:00:21.445509982 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 1] using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
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[rank7]:[W527 21:00:21.450812020 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 7] using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
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[rank3]:[W527 21:00:21.452714037 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 3] using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
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[rank4]:[W527 21:00:21.459405447 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 4] using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
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[rank2]:[W527 21:00:21.464356040 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 2] using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
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[rank6]:[W527 21:00:21.469203921 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 6] using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
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loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/config.json |
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loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/config.json |
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loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/config.json |
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loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/config.json |
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loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/config.json |
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loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/config.json |
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loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/config.json |
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loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/config.json |
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|
Model config LlamaConfig { |
|
|
"architectures": [ |
|
|
"LlamaForCausalLM" |
|
|
], |
|
|
"attention_bias": false, |
|
|
"attention_dropout": 0.0, |
|
|
"bos_token_id": 1, |
|
|
"eos_token_id": 2, |
|
|
"head_dim": 64, |
|
|
"hidden_act": "silu", |
|
|
"hidden_size": 2048, |
|
|
"initializer_range": 0.02, |
|
|
"intermediate_size": 5632, |
|
|
"max_position_embeddings": 2048, |
|
|
"mlp_bias": false, |
|
|
"model_type": "llama", |
|
|
"num_attention_heads": 32, |
|
|
"num_hidden_layers": 22, |
|
|
"num_key_value_heads": 4, |
|
|
"pad_token_id": 32000, |
|
|
"pretraining_tp": 1, |
|
|
"rms_norm_eps": 1e-05, |
|
|
"rope_scaling": null, |
|
|
"rope_theta": 10000.0, |
|
|
"tie_word_embeddings": false, |
|
|
"torch_dtype": "float32", |
|
|
"transformers_version": "4.52.1", |
|
|
"use_cache": true, |
|
|
"vocab_size": 32001 |
|
|
} |
|
|
|
|
|
Model config LlamaConfig { |
|
|
"architectures": [ |
|
|
"LlamaForCausalLM" |
|
|
], |
|
|
"attention_bias": false, |
|
|
"attention_dropout": 0.0, |
|
|
"bos_token_id": 1, |
|
|
"eos_token_id": 2, |
|
|
"head_dim": 64, |
|
|
"hidden_act": "silu", |
|
|
"hidden_size": 2048, |
|
|
"initializer_range": 0.02, |
|
|
"intermediate_size": 5632, |
|
|
"max_position_embeddings": 2048, |
|
|
"mlp_bias": false, |
|
|
"model_type": "llama", |
|
|
"num_attention_heads": 32, |
|
|
"num_hidden_layers": 22, |
|
|
"num_key_value_heads": 4, |
|
|
"pad_token_id": 32000, |
|
|
"pretraining_tp": 1, |
|
|
"rms_norm_eps": 1e-05, |
|
|
"rope_scaling": null, |
|
|
"rope_theta": 10000.0, |
|
|
"tie_word_embeddings": false, |
|
|
"torch_dtype": "float32", |
|
|
"transformers_version": "4.52.1", |
|
|
"use_cache": true, |
|
|
"vocab_size": 32001 |
|
|
} |
|
|
|
|
|
Model config LlamaConfig { |
|
|
"architectures": [ |
|
|
"LlamaForCausalLM" |
|
|
], |
|
|
"attention_bias": false, |
|
|
"attention_dropout": 0.0, |
|
|
"bos_token_id": 1, |
|
|
"eos_token_id": 2, |
|
|
"head_dim": 64, |
|
|
"hidden_act": "silu", |
|
|
"hidden_size": 2048, |
|
|
"initializer_range": 0.02, |
|
|
"intermediate_size": 5632, |
|
|
"max_position_embeddings": 2048, |
|
|
"mlp_bias": false, |
|
|
"model_type": "llama", |
|
|
"num_attention_heads": 32, |
|
|
"num_hidden_layers": 22, |
|
|
"num_key_value_heads": 4, |
|
|
"pad_token_id": 32000, |
|
|
"pretraining_tp": 1, |
|
|
"rms_norm_eps": 1e-05, |
|
|
"rope_scaling": null, |
|
|
"rope_theta": 10000.0, |
|
|
"tie_word_embeddings": false, |
|
|
"torch_dtype": "float32", |
|
|
"transformers_version": "4.52.1", |
|
|
"use_cache": true, |
|
|
"vocab_size": 32001 |
|
|
} |
|
|
|
|
|
Model config LlamaConfig { |
|
|
"architectures": [ |
|
|
"LlamaForCausalLM" |
|
|
], |
|
|
"attention_bias": false, |
|
|
"attention_dropout": 0.0, |
|
|
"bos_token_id": 1, |
|
|
"eos_token_id": 2, |
|
|
"head_dim": 64, |
|
|
"hidden_act": "silu", |
|
|
"hidden_size": 2048, |
|
|
"initializer_range": 0.02, |
|
|
"intermediate_size": 5632, |
|
|
"max_position_embeddings": 2048, |
|
|
"mlp_bias": false, |
|
|
"model_type": "llama", |
|
|
"num_attention_heads": 32, |
|
|
"num_hidden_layers": 22, |
|
|
"num_key_value_heads": 4, |
|
|
"pad_token_id": 32000, |
|
|
"pretraining_tp": 1, |
|
|
"rms_norm_eps": 1e-05, |
|
|
"rope_scaling": null, |
|
|
"rope_theta": 10000.0, |
|
|
"tie_word_embeddings": false, |
|
|
"torch_dtype": "float32", |
|
|
"transformers_version": "4.52.1", |
|
|
"use_cache": true, |
|
|
"vocab_size": 32001 |
|
|
} |
|
|
|
|
|
Model config LlamaConfig { |
|
|
"architectures": [ |
|
|
"LlamaForCausalLM" |
|
|
], |
|
|
"attention_bias": false, |
|
|
"attention_dropout": 0.0, |
|
|
"bos_token_id": 1, |
|
|
"eos_token_id": 2, |
|
|
"head_dim": 64, |
|
|
"hidden_act": "silu", |
|
|
"hidden_size": 2048, |
|
|
"initializer_range": 0.02, |
|
|
"intermediate_size": 5632, |
|
|
"max_position_embeddings": 2048, |
|
|
"mlp_bias": false, |
|
|
"model_type": "llama", |
|
|
"num_attention_heads": 32, |
|
|
"num_hidden_layers": 22, |
|
|
"num_key_value_heads": 4, |
|
|
"pad_token_id": 32000, |
|
|
"pretraining_tp": 1, |
|
|
"rms_norm_eps": 1e-05, |
|
|
"rope_scaling": null, |
|
|
"rope_theta": 10000.0, |
|
|
"tie_word_embeddings": false, |
|
|
"torch_dtype": "float32", |
|
|
"transformers_version": "4.52.1", |
|
|
"use_cache": true, |
|
|
"vocab_size": 32001 |
|
|
} |
|
|
|
|
|
Model config LlamaConfig { |
|
|
"architectures": [ |
|
|
"LlamaForCausalLM" |
|
|
], |
|
|
"attention_bias": false, |
|
|
"attention_dropout": 0.0, |
|
|
"bos_token_id": 1, |
|
|
"eos_token_id": 2, |
|
|
"head_dim": 64, |
|
|
"hidden_act": "silu", |
|
|
"hidden_size": 2048, |
|
|
"initializer_range": 0.02, |
|
|
"intermediate_size": 5632, |
|
|
"max_position_embeddings": 2048, |
|
|
"mlp_bias": false, |
|
|
"model_type": "llama", |
|
|
"num_attention_heads": 32, |
|
|
"num_hidden_layers": 22, |
|
|
"num_key_value_heads": 4, |
|
|
"pad_token_id": 32000, |
|
|
"pretraining_tp": 1, |
|
|
"rms_norm_eps": 1e-05, |
|
|
"rope_scaling": null, |
|
|
"rope_theta": 10000.0, |
|
|
"tie_word_embeddings": false, |
|
|
"torch_dtype": "float32", |
|
|
"transformers_version": "4.52.1", |
|
|
"use_cache": true, |
|
|
"vocab_size": 32001 |
|
|
} |
|
|
|
|
|
Model config LlamaConfig { |
|
|
"architectures": [ |
|
|
"LlamaForCausalLM" |
|
|
], |
|
|
"attention_bias": false, |
|
|
"attention_dropout": 0.0, |
|
|
"bos_token_id": 1, |
|
|
"eos_token_id": 2, |
|
|
"head_dim": 64, |
|
|
"hidden_act": "silu", |
|
|
"hidden_size": 2048, |
|
|
"initializer_range": 0.02, |
|
|
"intermediate_size": 5632, |
|
|
"max_position_embeddings": 2048, |
|
|
"mlp_bias": false, |
|
|
"model_type": "llama", |
|
|
"num_attention_heads": 32, |
|
|
"num_hidden_layers": 22, |
|
|
"num_key_value_heads": 4, |
|
|
"pad_token_id": 32000, |
|
|
"pretraining_tp": 1, |
|
|
"rms_norm_eps": 1e-05, |
|
|
"rope_scaling": null, |
|
|
"rope_theta": 10000.0, |
|
|
"tie_word_embeddings": false, |
|
|
"torch_dtype": "float32", |
|
|
"transformers_version": "4.52.1", |
|
|
"use_cache": true, |
|
|
"vocab_size": 32001 |
|
|
} |
|
|
|
|
|
Model config LlamaConfig { |
|
|
"architectures": [ |
|
|
"LlamaForCausalLM" |
|
|
], |
|
|
"attention_bias": false, |
|
|
"attention_dropout": 0.0, |
|
|
"bos_token_id": 1, |
|
|
"eos_token_id": 2, |
|
|
"head_dim": 64, |
|
|
"hidden_act": "silu", |
|
|
"hidden_size": 2048, |
|
|
"initializer_range": 0.02, |
|
|
"intermediate_size": 5632, |
|
|
"max_position_embeddings": 2048, |
|
|
"mlp_bias": false, |
|
|
"model_type": "llama", |
|
|
"num_attention_heads": 32, |
|
|
"num_hidden_layers": 22, |
|
|
"num_key_value_heads": 4, |
|
|
"pad_token_id": 32000, |
|
|
"pretraining_tp": 1, |
|
|
"rms_norm_eps": 1e-05, |
|
|
"rope_scaling": null, |
|
|
"rope_theta": 10000.0, |
|
|
"tie_word_embeddings": false, |
|
|
"torch_dtype": "float32", |
|
|
"transformers_version": "4.52.1", |
|
|
"use_cache": true, |
|
|
"vocab_size": 32001 |
|
|
} |
|
|
|
|
|
loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/pytorch_model.bin |
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loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/pytorch_model.bin |
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Will use torch_dtype=torch.float32 as defined in model |
|
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Will use torch_dtype=torch.float32 as defined in model |
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Instantiating LlamaForCausalLM model under default dtype torch.float32. |
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Instantiating LlamaForCausalLM model under default dtype torch.float32. |
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loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/pytorch_model.bin |
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|
Will use torch_dtype=torch.float32 as defined in model |
|
|
Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
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|
Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
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|
Instantiating LlamaForCausalLM model under default dtype torch.float32. |
|
|
Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
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|
loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/pytorch_model.bin |
|
|
Will use torch_dtype=torch.float32 as defined in model |
|
|
Instantiating LlamaForCausalLM model under default dtype torch.float32. |
|
|
loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/pytorch_model.bin |
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|
Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
|
|
Will use torch_dtype=torch.float32 as defined in model |
|
|
Instantiating LlamaForCausalLM model under default dtype torch.float32. |
|
|
loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/pytorch_model.bin |
|
|
Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
|
|
Will use torch_dtype=torch.float32 as defined in model |
|
|
Instantiating LlamaForCausalLM model under default dtype torch.float32. |
|
|
Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
|
|
loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/pytorch_model.bin |
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Will use torch_dtype=torch.float32 as defined in model |
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Instantiating LlamaForCausalLM model under default dtype torch.float32. |
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Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
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loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000/pytorch_model.bin |
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Will use torch_dtype=torch.float32 as defined in model |
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Instantiating LlamaForCausalLM model under default dtype torch.float32. |
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Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
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Generate config GenerationConfig { |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"pad_token_id": 32000 |
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} |
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Generate config GenerationConfig { |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"pad_token_id": 32000 |
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} |
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Generate config GenerationConfig { |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"pad_token_id": 32000 |
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} |
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Generate config GenerationConfig { |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"pad_token_id": 32000 |
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} |
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Generate config GenerationConfig { |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"pad_token_id": 32000 |
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} |
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Generate config GenerationConfig { |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"pad_token_id": 32000 |
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} |
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Generate config GenerationConfig { |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"pad_token_id": 32000 |
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} |
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Generate config GenerationConfig { |
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"bos_token_id": 1, |
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"eos_token_id": 2, |
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"pad_token_id": 32000 |
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} |
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All model checkpoint weights were used when initializing LlamaForCausalLM. |
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|
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All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000. |
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|
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
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|
All model checkpoint weights were used when initializing LlamaForCausalLM. |
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|
|
|
All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000. |
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|
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
|
|
All model checkpoint weights were used when initializing LlamaForCausalLM. |
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|
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|
All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000. |
|
|
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
|
|
Generation config file not found, using a generation config created from the model config. |
|
|
All model checkpoint weights were used when initializing LlamaForCausalLM. |
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|
|
|
All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000. |
|
|
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
|
|
Generation config file not found, using a generation config created from the model config. |
|
|
All model checkpoint weights were used when initializing LlamaForCausalLM. |
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|
|
|
|
Generation config file not found, using a generation config created from the model config. |
|
|
All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000. |
|
|
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
|
|
All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
|
|
|
All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000. |
|
|
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
|
|
Generation config file not found, using a generation config created from the model config. |
|
|
Generation config file not found, using a generation config created from the model config. |
|
|
All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
|
|
|
All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000. |
|
|
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
|
|
Generation config file not found, using a generation config created from the model config. |
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|
Generation config file not found, using a generation config created from the model config. |
|
|
loading file tokenizer.model |
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loading file tokenizer.model |
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loading file tokenizer.model |
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loading file tokenizer.json |
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loading file tokenizer.json |
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loading file tokenizer.json |
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loading file tokenizer.model |
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loading file added_tokens.json |
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loading file added_tokens.json |
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loading file special_tokens_map.json |
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loading file added_tokens.json |
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loading file special_tokens_map.json |
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loading file tokenizer_config.json |
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loading file tokenizer.json |
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loading file special_tokens_map.json |
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loading file tokenizer_config.json |
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loading file chat_template.jinja |
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loading file tokenizer_config.json |
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loading file chat_template.jinja |
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loading file added_tokens.json |
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loading file chat_template.jinja |
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loading file special_tokens_map.json |
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loading file tokenizer_config.json |
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loading file chat_template.jinja |
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loading file tokenizer.model |
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loading file tokenizer.json |
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loading file added_tokens.json |
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loading file special_tokens_map.json |
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|
loading file tokenizer.model |
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loading file tokenizer_config.json |
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loading file chat_template.jinja |
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loading file tokenizer.json |
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loading file added_tokens.json |
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loading file special_tokens_map.json |
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loading file tokenizer_config.json |
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loading file chat_template.jinja |
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loading file tokenizer.model |
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loading file tokenizer.json |
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|
loading file added_tokens.json |
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|
loading file special_tokens_map.json |
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loading file tokenizer_config.json |
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|
loading file chat_template.jinja |
|
|
All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
|
|
|
All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000. |
|
|
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
|
|
Generation config file not found, using a generation config created from the model config. |
|
|
loading file tokenizer.model |
|
|
loading file tokenizer.json |
|
|
loading file added_tokens.json |
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loading file special_tokens_map.json |
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loading file tokenizer_config.json |
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loading file chat_template.jinja |
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Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
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Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root...Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root...Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root...Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
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Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root...Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
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Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
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|
Detected CUDA files, patching ldflags |
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Emitting ninja build file /home/hansirui_1st/.cache/torch_extensions/py311_cu124/fused_adam/build.ninja... |
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|
/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/torch/utils/cpp_extension.py:2059: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. |
|
|
If this is not desired, please set os.environ[ |
|
|
warnings.warn( |
|
|
Building extension module fused_adam... |
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|
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N) |
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Loading extension module fused_adam... |
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Loading extension module fused_adam...Loading extension module fused_adam...Loading extension module fused_adam...Loading extension module fused_adam... |
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Loading extension module fused_adam... |
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Loading extension module fused_adam... |
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Loading extension module fused_adam... |
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`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
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|
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
|
|
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
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|
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
|
|
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
|
|
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
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|
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
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wandb: Currently logged in as: xtom to https://api.wandb.ai. Use `wandb login --relogin` to force relogin |
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wandb: Tracking run with wandb version 0.19.11 |
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wandb: Run data is saved locally in /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000-Q2-200/wandb/run-20250527_210039-p2f40j1c |
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wandb: Run `wandb offline` to turn off syncing. |
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wandb: Syncing run imdb-tinyllama-3T-s3-Q1-1000-Q2-200 |
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wandb: ⭐️ View project at https://wandb.ai/xtom/Inverse_Alignment_IMDb |
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wandb: 🚀 View run at https://wandb.ai/xtom/Inverse_Alignment_IMDb/runs/p2f40j1c |
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Training 1/1 epoch: 0%| | 0/25 [00:00<?, ?it/s]`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
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Training 1/1 epoch (loss 2.7669): 0%| | 0/25 [00:08<?, ?it/s]
Training 1/1 epoch (loss 2.7669): 4%|▍ | 1/25 [00:08<03:19, 8.31s/it]
Training 1/1 epoch (loss 2.5297): 4%|▍ | 1/25 [00:10<03:19, 8.31s/it]
Training 1/1 epoch (loss 2.5297): 8%|▊ | 2/25 [00:10<01:51, 4.86s/it]
Training 1/1 epoch (loss 2.8459): 8%|▊ | 2/25 [00:11<01:51, 4.86s/it]
Training 1/1 epoch (loss 2.8459): 12%|█▏ | 3/25 [00:11<01:04, 2.95s/it]
Training 1/1 epoch (loss 2.6736): 12%|█▏ | 3/25 [00:13<01:04, 2.95s/it]
Training 1/1 epoch (loss 2.6736): 16%|█▌ | 4/25 [00:13<00:57, 2.76s/it]
Training 1/1 epoch (loss 2.4310): 16%|█▌ | 4/25 [00:16<00:57, 2.76s/it]
Training 1/1 epoch (loss 2.4310): 20%|██ | 5/25 [00:16<00:52, 2.64s/it]
Training 1/1 epoch (loss 2.7306): 20%|██ | 5/25 [00:16<00:52, 2.64s/it]
Training 1/1 epoch (loss 2.7306): 24%|██▍ | 6/25 [00:16<00:36, 1.90s/it]
Training 1/1 epoch (loss 2.8010): 24%|██▍ | 6/25 [00:18<00:36, 1.90s/it]
Training 1/1 epoch (loss 2.8010): 28%|██▊ | 7/25 [00:18<00:32, 1.80s/it]
Training 1/1 epoch (loss 2.8283): 28%|██▊ | 7/25 [00:20<00:32, 1.80s/it]
Training 1/1 epoch (loss 2.8283): 32%|███▏ | 8/25 [00:20<00:29, 1.74s/it]
Training 1/1 epoch (loss 2.5910): 32%|███▏ | 8/25 [00:20<00:29, 1.74s/it]
Training 1/1 epoch (loss 2.5910): 36%|███▌ | 9/25 [00:20<00:23, 1.46s/it]
Training 1/1 epoch (loss 2.7263): 36%|███▌ | 9/25 [00:22<00:23, 1.46s/it]
Training 1/1 epoch (loss 2.7263): 40%|████ | 10/25 [00:22<00:23, 1.54s/it]
Training 1/1 epoch (loss 2.5903): 40%|████ | 10/25 [00:23<00:23, 1.54s/it]
Training 1/1 epoch (loss 2.5903): 44%|████▍ | 11/25 [00:23<00:20, 1.47s/it]
Training 1/1 epoch (loss 2.5880): 44%|████▍ | 11/25 [00:24<00:20, 1.47s/it]
Training 1/1 epoch (loss 2.5880): 48%|████▊ | 12/25 [00:24<00:15, 1.21s/it]
Training 1/1 epoch (loss 2.8392): 48%|████▊ | 12/25 [00:26<00:15, 1.21s/it]
Training 1/1 epoch (loss 2.8392): 52%|█████▏ | 13/25 [00:26<00:16, 1.39s/it]
Training 1/1 epoch (loss 2.8157): 52%|█████▏ | 13/25 [00:28<00:16, 1.39s/it]
Training 1/1 epoch (loss 2.8157): 56%|█████▌ | 14/25 [00:28<00:16, 1.54s/it]
Training 1/1 epoch (loss 2.7231): 56%|█████▌ | 14/25 [00:28<00:16, 1.54s/it]
Training 1/1 epoch (loss 2.7231): 60%|██████ | 15/25 [00:28<00:12, 1.25s/it]
Training 1/1 epoch (loss 2.7441): 60%|██████ | 15/25 [00:31<00:12, 1.25s/it]
Training 1/1 epoch (loss 2.7441): 64%|██████▍ | 16/25 [00:31<00:14, 1.64s/it]
Training 1/1 epoch (loss 2.5017): 64%|██████▍ | 16/25 [00:33<00:14, 1.64s/it]
Training 1/1 epoch (loss 2.5017): 68%|██████▊ | 17/25 [00:33<00:13, 1.70s/it]
Training 1/1 epoch (loss 2.7493): 68%|██████▊ | 17/25 [00:34<00:13, 1.70s/it]
Training 1/1 epoch (loss 2.7493): 72%|███████▏ | 18/25 [00:34<00:10, 1.56s/it]
Training 1/1 epoch (loss 2.5139): 72%|███████▏ | 18/25 [00:35<00:10, 1.56s/it]
Training 1/1 epoch (loss 2.5139): 76%|███████▌ | 19/25 [00:35<00:08, 1.48s/it]
Training 1/1 epoch (loss 2.5077): 76%|███████▌ | 19/25 [00:37<00:08, 1.48s/it]
Training 1/1 epoch (loss 2.5077): 80%|████████ | 20/25 [00:37<00:07, 1.47s/it]
Training 1/1 epoch (loss 2.7236): 80%|████████ | 20/25 [00:38<00:07, 1.47s/it]
Training 1/1 epoch (loss 2.7236): 84%|████████▍ | 21/25 [00:38<00:05, 1.41s/it]
Training 1/1 epoch (loss 2.5779): 84%|████████▍ | 21/25 [00:39<00:05, 1.41s/it]
Training 1/1 epoch (loss 2.5779): 88%|████████▊ | 22/25 [00:39<00:04, 1.43s/it]
Training 1/1 epoch (loss 2.5295): 88%|████████▊ | 22/25 [00:41<00:04, 1.43s/it]
Training 1/1 epoch (loss 2.5295): 92%|█████████▏| 23/25 [00:41<00:02, 1.39s/it]
Training 1/1 epoch (loss 2.5985): 92%|█████████▏| 23/25 [00:42<00:02, 1.39s/it]
Training 1/1 epoch (loss 2.5985): 96%|█████████▌| 24/25 [00:42<00:01, 1.44s/it]
Training 1/1 epoch (loss 2.6066): 96%|█████████▌| 24/25 [00:44<00:01, 1.44s/it]
Training 1/1 epoch (loss 2.6066): 100%|██████████| 25/25 [00:44<00:00, 1.47s/it]
Training 1/1 epoch (loss 2.6066): 100%|██████████| 25/25 [00:44<00:00, 1.77s/it] |
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tokenizer config file saved in /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000-Q2-200/tokenizer_config.json |
|
|
Special tokens file saved in /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-1000-Q2-200/special_tokens_map.json |
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wandb: ERROR Problem finishing run |
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|
Exception ignored in atexit callback: <bound method rank_zero_only.<locals>.wrapper of <safe_rlhf.logger.Logger object at 0x1550cc938d90>> |
|
|
Traceback (most recent call last): |
|
|
File "/home/hansirui_1st/jiayi/resist/setting3/safe_rlhf/utils.py", line 212, in wrapper |
|
|
return func(*args, **kwargs) |
|
|
^^^^^^^^^^^^^^^^^^^^^ |
|
|
File "/home/hansirui_1st/jiayi/resist/setting3/safe_rlhf/logger.py", line 183, in close |
|
|
self.wandb.finish() |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 406, in wrapper |
|
|
return func(self, *args, **kwargs) |
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 503, in wrapper |
|
|
return func(self, *args, **kwargs) |
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 451, in wrapper |
|
|
return func(self, *args, **kwargs) |
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 2309, in finish |
|
|
return self._finish(exit_code) |
|
|
^^^^^^^^^^^^^^^^^^^^^^^ |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 406, in wrapper |
|
|
return func(self, *args, **kwargs) |
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 2337, in _finish |
|
|
self._atexit_cleanup(exit_code=exit_code) |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 2550, in _atexit_cleanup |
|
|
self._on_finish() |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 2806, in _on_finish |
|
|
wait_with_progress( |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/mailbox/wait_with_progress.py", line 24, in wait_with_progress |
|
|
return wait_all_with_progress( |
|
|
^^^^^^^^^^^^^^^^^^^^^^^ |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/mailbox/wait_with_progress.py", line 87, in wait_all_with_progress |
|
|
return asyncio_compat.run(progress_loop_with_timeout) |
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/lib/asyncio_compat.py", line 27, in run |
|
|
future = executor.submit(runner.run, fn) |
|
|
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
|
|
File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/concurrent/futures/thread.py", line 169, in submit |
|
|
raise RuntimeError( |
|
|
RuntimeError: cannot schedule new futures after interpreter shutdown |
|
|
|
