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adapter/README.md ADDED
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+ ---
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+ license: apache-2.0
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ base_model: Lambent/cosmoem-4x1b
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+ model-index:
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+ - name: lora-out
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.4.0`
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+ ```yaml
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+ base_model: Lambent/cosmoem-4x1b
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: LlamaTokenizer
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+ trust_remote_code: true
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+
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+ load_in_8bit: false
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+ load_in_4bit: false
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+ strict: false
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+
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+ datasets:
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+ - path: HuggingFaceTB/cosmopedia-100k
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+ type: completion
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+ - path: Vezora/Tested-22k-Python-Alpaca
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+ type: alpaca
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+ dataset_prepared_path: prepared-cosmoem
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+ val_set_size: 0.05
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+ output_dir: ./lora-out
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+
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+ sequence_len: 2048
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+ sample_packing: true
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+ eval_sample_packing: false
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+ pad_to_sequence_len: true
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+
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+ adapter: lora
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+ lora_model_dir:
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+ lora_r: 128
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+ lora_alpha: 16
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+ lora_dropout: 0.1
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+ lora_target_linear: true
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+ lora_fan_in_fan_out:
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+
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+ wandb_project: cosmoem-cosmo100
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_name:
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 1
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+ micro_batch_size: 16
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+ num_epochs: 1
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+ optimizer: adamw_bnb_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.001
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+
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+ train_on_inputs: false
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+ group_by_length: false
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+ bf16: auto
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+ fp16:
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+ tf32: false
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+
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+ gradient_checkpointing: true
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+ early_stopping_patience:
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+ resume_from_checkpoint:
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+ local_rank:
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+ logging_steps: 1
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+ xformers_attention:
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+ flash_attention: true
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+
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+ loss_watchdog_threshold: 2.0
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+ loss_watchdog_patience: 3
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+
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+ warmup_steps: 10
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+ evals_per_epoch: 4
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+ saves_per_epoch: 1
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+ debug:
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+ deepspeed:
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+ weight_decay: 0.002
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+ fsdp:
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+ fsdp_config:
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+ special_tokens:
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+
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+ ```
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+
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+ </details><br>
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+
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+ # lora-out
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+
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+ This model is a fine-tuned version of [Lambent/cosmoem-4x1b](https://huggingface.co/Lambent/cosmoem-4x1b) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9382
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 10
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.9599 | 0.0 | 1 | 0.9550 |
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+ | 0.9077 | 0.25 | 672 | 0.9459 |
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+ | 0.919 | 0.5 | 1344 | 0.9439 |
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+ | 0.9228 | 0.75 | 2016 | 0.9391 |
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+ | 0.9236 | 1.0 | 2688 | 0.9382 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.9.0
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+ - Transformers 4.40.0.dev0
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+ - Pytorch 2.1.2+cu118
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.0
adapter/adapter_config.json ADDED
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+ {
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+ "alpha_pattern": {},
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+ "auto_mapping": null,
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+ "base_model_name_or_path": "Lambent/cosmoem-4x1b",
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+ "bias": "none",
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+ "fan_in_fan_out": null,
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "layers_pattern": null,
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+ "layers_to_transform": null,
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+ "loftq_config": {},
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+ "lora_alpha": 16,
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+ "lora_dropout": 0.1,
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+ "megatron_config": null,
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+ "megatron_core": "megatron.core",
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+ "modules_to_save": null,
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+ "peft_type": "LORA",
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+ "r": 128,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "v_proj",
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+ "q_proj",
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+ "o_proj",
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+ "w2",
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+ "gate",
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+ "w3",
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+ "w1",
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+ "k_proj"
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+ ],
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+ "task_type": "CAUSAL_LM",
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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adapter/config.json ADDED
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+ {
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+ "_name_or_path": "Lambent/cosmoem-4x1b",
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+ "MixtralForCausalLM"
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+ "vocab_size": 32000
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+ }
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