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--- |
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license: mit |
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library_name: peft |
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tags: |
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- trl |
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- dpo |
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- generated_from_trainer |
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base_model: HuggingFaceH4/mistral-7b-sft-beta |
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model-index: |
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- name: zephyr-deita-kto-3ep-v3-r1024-bsz8 |
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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: `0.3.0` |
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```yaml |
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base_model: HuggingFaceH4/mistral-7b-sft-beta |
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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: false |
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load_in_4bit: false |
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strict: false |
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rl: kto_pair |
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datasets: |
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- path: winglian/deita-nectar |
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split: train_dpo |
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type: zephyr.nectar |
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_test_datasets: |
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- path: winglian/deita-nectar |
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split: test_dpo |
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type: zephyr.nectar |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.0 |
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output_dir: ./zephyr-deita-kto-3ep-v3-r1024-bsz8 |
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save_total_limit: 3 |
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hub_model_id: openaccess-ai-collective/kto-zephyr-deita-nectar |
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adapter: lora |
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lora_model_dir: |
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sequence_len: 2048 |
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sample_packing: false |
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pad_to_sequence_len: false |
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lora_r: 1024 |
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lora_alpha: 512 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_modules_to_save: |
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lora_fan_in_fan_out: |
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lora_target_modules: |
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- gate_proj |
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- down_proj |
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- up_proj |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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wandb_project: dpo-zephyr-deita-nectar |
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wandb_entity: oaaic |
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wandb_watch: |
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wandb_run_id: |
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wandb_name: kto-3ep-v3-r1024-bsz8-lr1.4e-5 |
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wandb_log_model: |
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gradient_accumulation_steps: 1 |
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micro_batch_size: 2 |
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num_epochs: 3 |
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optimizer: paged_adamw_8bit |
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adam_beta2: 0.95 |
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adam_epsilion: 0.00001 |
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lr_scheduler: linear |
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learning_rate: 1.414e-5 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: true |
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fp16: false |
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tf32: true |
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gradient_checkpointing: true |
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gradient_checkpoint_kwargs: |
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use_reentrant: 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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warmup_steps: 10 |
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eval_steps: |
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eval_table_size: |
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eval_table_max_new_tokens: 128 |
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save_steps: 45 |
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debug: |
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deepspeed: |
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weight_decay: 0.1 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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save_safetensors: true |
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dataloader_num_workers: 16 |
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dataloader_pin_memory: true |
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``` |
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</details><br> |
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# zephyr-deita-kto-3ep-v3-r1024-bsz8 |
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This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingface.co/HuggingFaceH4/mistral-7b-sft-beta) 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: 1.414e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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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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- total_train_batch_size: 8 |
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- total_eval_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 10 |
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- training_steps: 3230 |
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### Training results |
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### Framework versions |
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- PEFT 0.7.0 |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
