Anim Mina
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End of training
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- adapter_model.bin +3 -0
README.md
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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: cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
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model-index:
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- name: cheater-7b
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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: cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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load_in_8bit: true
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load_in_4bit: false
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strict: false
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datasets:
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- path: ./julia/data.jsonl
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type: sharegpt
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conversation: chatml
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dataset_prepared_path: ./julia/prepared_data
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chat_template: chatml
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val_set_size: 0.05
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output_dir: ./julia/lora-out
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hub_model_id: animmina/cheater-7b
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hub_strategy: every_save
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hf_use_auth_token: true
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sequence_len: 2048
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sample_packing: true
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pad_to_sequence_len: true
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eval_sample_packing: false
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adapter: lora
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lora_model_dir:
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lora_r: 8
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_linear: true
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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: cheater-7b
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wandb_entity:
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wandb_watch:
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wandb_name: v02
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wandb_log_model:
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gradient_accumulation_steps: 1
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micro_batch_size: 4
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num_epochs: 4
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.00003
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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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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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warmup_steps: 10
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evals_per_epoch: 4
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eval_table_size:
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eval_max_new_tokens: 128
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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bos_token: "<s>"
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eos_token: "<|im_end|>"
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unk_token: "<unk>"
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```
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</details><br>
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# cheater-7b
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This model is a fine-tuned version of [cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5741
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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: 3e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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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: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.554 | 0.04 | 1 | 0.6521 |
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| 0.4152 | 0.26 | 7 | 0.6499 |
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| 0.3984 | 0.52 | 14 | 0.6283 |
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| 0.4133 | 0.78 | 21 | 0.6140 |
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| 0.3772 | 1.04 | 28 | 0.5951 |
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| 0.3855 | 1.22 | 35 | 0.5869 |
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| 0.4077 | 1.48 | 42 | 0.5840 |
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| 0.3104 | 1.74 | 49 | 0.5793 |
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| 0.3345 | 2.0 | 56 | 0.5776 |
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| 0.3207 | 2.19 | 63 | 0.5761 |
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| 0.3679 | 2.44 | 70 | 0.5784 |
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| 0.3593 | 2.7 | 77 | 0.5781 |
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| 0.2391 | 2.96 | 84 | 0.5761 |
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| 0.3329 | 3.15 | 91 | 0.5743 |
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| 0.2636 | 3.41 | 98 | 0.5744 |
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| 0.3114 | 3.67 | 105 | 0.5741 |
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### Framework versions
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- PEFT 0.9.0
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- Transformers 4.38.2
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- Pytorch 2.1.2+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.0
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adapter_model.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:9165080527686729d26aaaf8d6a848a2dd5c613a2f51146d57b882e461def334
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size 84047370
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