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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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- axolotl |
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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-v0.1 |
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model-index: |
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- name: mistral-tenglish-april5_2 |
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results: [] |
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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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[<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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axolotl version: `0.4.0` |
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```yaml |
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base_model: mistralai/Mistral-7B-v0.1 |
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base_model_config: mistralai/Mistral-7B-v0.1 |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_mistral_derived_model: true |
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load_in_8bit: true |
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load_in_4bit: false |
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bf16: true |
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fp16: false |
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tf32: false |
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bfloat16: true |
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datasets: |
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- path: indiehackers/telugu_romanized_2048_mistral |
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type: completion |
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field: text |
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#dataset_prepared_path: ./dataset_tt23 |
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hub_model_id: indiehackers/mistral-tenglish-april5_2 |
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hf_use_auth_token: true |
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val_set_size: 0.0 |
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sequence_len: 2048 |
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pad_to_sequence_len: true |
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sample_packing: true |
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# eval_sample_packing: false |
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adapter: lora |
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lora_r: 128 |
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lora_alpha: 256 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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wandb_project: mistral-tenglish |
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wandb_entity: team-nik |
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#wandb_log_model: end |
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output_dir: ./mistral-tenglish-out |
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# Training hyperparameters |
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gradient_accumulation_steps: 2 |
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micro_batch_size: 7 |
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warmup_steps: 50 |
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learning_rate: 0.00002 |
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logging_steps: 1 |
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evals_per_epoch: |
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save_strategy: steps |
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save_steps: 100 |
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save_total_limit: 10 |
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num_epochs: 1 |
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#max_steps: 162945 |
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# eval_table_size: |
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# eval_max_new_tokens: 128 |
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train_on_inputs: false |
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group_by_length: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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lr_scheduler: linear |
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optimizer: adamw_bnb_8bit |
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weight_decay: 0.01 |
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xformers_attention: |
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flash_attention: true |
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resume_from_checkpoint: |
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auto_resume_from_checkpoints: true |
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local_rank: |
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fsdp: |
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fsdp_config: |
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deepspeed: |
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debug: |
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strict: false |
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# load_best_model_at_end: True |
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max_grad_norm: 0.3 |
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``` |
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</details><br> |
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# mistral-tenglish-april5_2 |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 7 |
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- eval_batch_size: 7 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 56 |
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- total_eval_batch_size: 28 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 1 |
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### Training results |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.0 |
