1-lock
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e7732a70-ca77-4feb-8897-396abc6097f1

@@ -1,168 +1,182 @@
----
-library_name: peft
-license: apache-2.0
-base_model: Qwen/Qwen2.5-0.5B
-tags:
-- axolotl
-- generated_from_trainer
-model-index:
-- name: e7732a70-ca77-4feb-8897-396abc6097f1
-  results: []
----
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
-<details><summary>See axolotl config</summary>
-axolotl version: `0.4.1`
-```yaml
-adapter: lora
-base_model: Qwen/Qwen2.5-0.5B
-bf16: auto
-chat_template: llama3
-cosine_min_lr_ratio: 0.1
-data_processes: 4
-dataset_prepared_path: null
-datasets:
-- data_files:
-  - 3055aeccdac79880_train_data.json
-  ds_type: json
-  field: source
-  num_proc: 4
-  path: /workspace/input_data/3055aeccdac79880_train_data.json
-  streaming: true
-  type: completion
-debug: null
-deepspeed: null
-device_map: balanced
-do_eval: true
-early_stopping_patience: 1
-eval_batch_size: 1
-eval_sample_packing: false
-eval_steps: 25
-evaluation_strategy: steps
-flash_attention: false
-fp16: null
-fsdp: null
-fsdp_config: null
-gradient_accumulation_steps: 16
-gradient_checkpointing: true
-group_by_length: true
-hub_model_id: dsakerkwq/e7732a70-ca77-4feb-8897-396abc6097f1
-hub_strategy: checkpoint
-hub_token: null
-learning_rate: 0.0001
-load_in_4bit: false
-load_in_8bit: false
-local_rank: null
-logging_steps: 1
-lora_alpha: 64
-lora_dropout: 0.05
-lora_fan_in_fan_out: null
-lora_model_dir: null
-lora_r: 32
-lora_target_linear: true
-lora_target_modules:
-- q_proj
-- v_proj
-lr_scheduler: cosine
-max_grad_norm: 1.0
-max_memory:
-  0: 75GB
-  1: 75GB
-  2: 75GB
-  3: 75GB
-max_steps: 50
-micro_batch_size: 2
-mixed_precision: bf16
-mlflow_experiment_name: /tmp/3055aeccdac79880_train_data.json
-model_type: AutoModelForCausalLM
-num_epochs: 3
-optim_args:
-  adam_beta1: 0.9
-  adam_beta2: 0.95
-  adam_epsilon: 1e-5
-optimizer: adamw_torch
-output_dir: miner_id_24
-pad_to_sequence_len: true
-resume_from_checkpoint: null
-s2_attention: null
-sample_packing: false
-save_steps: 25
-save_strategy: steps
-sequence_len: 2048
-strict: false
-tf32: false
-tokenizer_type: AutoTokenizer
-torch_compile: false
-train_on_inputs: false
-trust_remote_code: true
-val_set_size: 50
-wandb_entity: null
-wandb_mode: online
-wandb_name: e7732a70-ca77-4feb-8897-396abc6097f1
-wandb_project: Public_TuningSN
-wandb_runid: e7732a70-ca77-4feb-8897-396abc6097f1
-warmup_ratio: 0.04
-weight_decay: 0.01
-xformers_attention: null
-```
-</details><br>
-# e7732a70-ca77-4feb-8897-396abc6097f1
-This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1251
-## Model description
-More information needed
-## Intended uses & limitations
-More information needed
-## Training and evaluation data
-More information needed
-## Training procedure
-### Training hyperparameters
-The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 2
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 4
-- gradient_accumulation_steps: 16
-- total_train_batch_size: 128
-- total_eval_batch_size: 4
-- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 2
-- training_steps: 50
-### Training results
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| 3.8364        | 0.0004 | 1    | 3.8023          |
-| 0.3892        | 0.0097 | 25   | 0.1337          |
-| 0.5574        | 0.0194 | 50   | 0.1251          |
-### Framework versions
-- PEFT 0.13.2
-- Transformers 4.46.0
-- Pytorch 2.5.0+cu124
-- Datasets 3.0.1
 - Tokenizers 0.20.1

+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen2.5-0.5B
+tags:
+- axolotl
+- generated_from_trainer
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+model-index:
+- name: e7732a70-ca77-4feb-8897-396abc6097f1
+  results: []
+---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+axolotl version: `0.4.1`
+```yaml
+adapter: lora
+base_model: Qwen/Qwen2.5-0.5B
+bf16: auto
+chat_template: llama3
+cosine_min_lr_ratio: 0.1
+data_processes: 4
+dataset_prepared_path: null
+datasets:
+- data_files:
+  - 3055aeccdac79880_train_data.json
+  ds_type: json
+  field: source
+  num_proc: 4
+  path: /workspace/input_data/3055aeccdac79880_train_data.json
+  streaming: true
+  type: completion
+debug: null
+deepspeed: null
+device_map: balanced
+do_eval: true
+early_stopping_patience: 1
+eval_batch_size: 1
+eval_sample_packing: false
+eval_steps: 25
+evaluation_strategy: steps
+flash_attention: false
+fp16: null
+fsdp: null
+fsdp_config: null
+gradient_accumulation_steps: 16
+gradient_checkpointing: true
+group_by_length: true
+hub_model_id: dsakerkwq/e7732a70-ca77-4feb-8897-396abc6097f1
+hub_strategy: checkpoint
+hub_token: null
+learning_rate: 0.0001
+load_in_4bit: false
+load_in_8bit: false
+local_rank: null
+logging_steps: 1
+lora_alpha: 64
+lora_dropout: 0.05
+lora_fan_in_fan_out: null
+lora_model_dir: null
+lora_r: 32
+lora_target_linear: true
+lora_target_modules:
+- q_proj
+- v_proj
+lr_scheduler: cosine
+max_grad_norm: 1.0
+max_memory:
+  0: 75GB
+  1: 75GB
+  2: 75GB
+  3: 75GB
+max_steps: 50
+micro_batch_size: 2
+mixed_precision: bf16
+mlflow_experiment_name: /tmp/3055aeccdac79880_train_data.json
+model_type: AutoModelForCausalLM
+num_epochs: 3
+optim_args:
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_epsilon: 1e-5
+optimizer: adamw_torch
+output_dir: miner_id_24
+pad_to_sequence_len: true
+resume_from_checkpoint: null
+s2_attention: null
+sample_packing: false
+save_steps: 25
+save_strategy: steps
+sequence_len: 2048
+strict: false
+tf32: false
+tokenizer_type: AutoTokenizer
+torch_compile: false
+train_on_inputs: false
+trust_remote_code: true
+val_set_size: 50
+wandb_entity: null
+wandb_mode: online
+wandb_name: e7732a70-ca77-4feb-8897-396abc6097f1
+wandb_project: Public_TuningSN
+wandb_runid: e7732a70-ca77-4feb-8897-396abc6097f1
+warmup_ratio: 0.04
+weight_decay: 0.01
+xformers_attention: null
+```
+</details><br>
+# e7732a70-ca77-4feb-8897-396abc6097f1
+This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1251
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 2
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- total_eval_batch_size: 4
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 2
+- training_steps: 50
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 3.8364        | 0.0004 | 1    | 3.8023          |
+| 0.3892        | 0.0097 | 25   | 0.1337          |
+| 0.5574        | 0.0194 | 50   | 0.1251          |
+### Framework versions
+- PEFT 0.13.2
+- Transformers 4.46.0
+- Pytorch 2.5.0+cu124
+- Datasets 3.0.1
 - Tokenizers 0.20.1