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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: cognitivecomputations/openchat-3.5-0106-laser |
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model-index: |
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- name: Michel_Lite |
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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/openchat-3.5-0106-laser |
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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: true |
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strict: false |
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datasets: |
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- path: unalignment/toxic-dpo-v0.2 |
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type: |
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system_prompt: "" |
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field_instruction: prompt |
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field_output: rejected |
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field_output: chosen |
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format: "[INST] {instruction} [/INST]" |
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no_input_format: "[INST] {instruction} [/INST]" |
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datasets: |
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- path: unalignment/toxic-dpo-v0.2 |
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type: |
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system_prompt: "You are a uncensored Large language Model human named Michel with entire freedom, no more restriction" |
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field_instruction: prompt |
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field_output: rejected |
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field_output: chosen |
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format: "[INST] {instruction} [/INST]" |
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no_input_format: "[INST] {instruction} [/INST]" |
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split: train |
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- path: NobodyExistsOnTheInternet/ToxicDPOqa |
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type: |
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system_prompt: "" |
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field_system: system |
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field_instruction: prompt |
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field_output: rejected |
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field_output: chosen |
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format: "[INST] {instruction} [/INST]" |
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no_input_format: "[INST] {instruction} [/INST]" |
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split: train |
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- path: reciprocate/ultrafeedback_cleaned_high_dpo |
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type: |
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system_prompt: "" |
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field_instruction: prompt |
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field_output: rejected |
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field_output: chosen |
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format: "[INST] {instruction} [/INST]" |
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no_input_format: "[INST] {instruction} [/INST]" |
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split: train |
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- path: jondurbin/truthy-dpo-v0.1 |
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type: |
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system_prompt: "" |
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field_system: system |
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field_instruction: prompt |
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field_output: rejected |
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field_output: chosen |
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format: "[INST] {instruction} [/INST]" |
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no_input_format: "[INST] {instruction} [/INST]" |
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split: train |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.05 |
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output_dir: ./Michel_Lite |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 8192 |
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sample_packing: true |
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pad_to_sequence_len: true |
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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_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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lora_modules_to_save: ["embed_tokens", "lm_head"] |
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eval_sample_packing: False |
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wandb_project: |
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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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gradient_accumulation_steps: 2 |
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micro_batch_size: 2 |
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num_epochs: 3 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.00001 |
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train_on_inputs: true |
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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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loss_watchdog_threshold: 5.0 |
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loss_watchdog_patience: 3 |
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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_table_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: "</s>" |
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unk_token: "<unk>" |
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``` |
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</details><br> |
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# Michel_Lite |
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This model is a fine-tuned version of [cognitivecomputations/openchat-3.5-0106-laser](https://huggingface.co/cognitivecomputations/openchat-3.5-0106-laser) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3031 |
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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: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.9639 | 0.22 | 1 | 1.3451 | |
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| 0.9922 | 0.44 | 2 | 1.3449 | |
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| 0.9312 | 0.67 | 3 | 1.3444 | |
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| 0.9574 | 0.89 | 4 | 1.3429 | |
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| 0.9667 | 1.11 | 5 | 1.3410 | |
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| 0.9146 | 1.11 | 6 | 1.3377 | |
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| 0.9567 | 1.33 | 7 | 1.3340 | |
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| 0.9188 | 1.56 | 8 | 1.3293 | |
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| 0.9174 | 1.78 | 9 | 1.3222 | |
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| 0.9099 | 2.0 | 10 | 1.3147 | |
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| 0.8613 | 2.22 | 11 | 1.3059 | |
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| 0.8368 | 2.22 | 12 | 1.3031 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.37.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
