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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: andysalerno/mistral-sft-v3 |
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model-index: |
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- name: rainbowfish-7B-v9 |
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results: [] |
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datasets: |
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- andysalerno/rainbowfish-v1 |
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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: andysalerno/mistral-sft-v3 |
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model_type: AutoModelForCausalLM |
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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: andysalerno/rainbowfish-v1 |
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type: |
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system_prompt: "" |
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field_system: system |
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field_instruction: input |
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field_output: output |
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format: "{instruction}" |
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no_input_format: "{instruction}" |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.005 |
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output_dir: ./lora-out-rainbow9 |
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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 # was true |
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eval_sample_packing: false |
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pad_to_sequence_len: false |
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padding_side: left |
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lora_r: 64 |
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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: |
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- embed_tokens |
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- lm_head |
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wandb_project: axolotl |
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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: 4 |
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micro_batch_size: 4 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 2e-5 |
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neftune_noise_alpha: 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: |
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tf32: false |
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gradient_checkpointing: true |
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gradient_checkpointing_kwargs: |
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use_reentrant: false |
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# early_stopping_patience: 3 |
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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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hub_strategy: "every_save" |
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hub_model_id: andysalerno/rainbowfish-v9-adapter |
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num_epochs: 4 |
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warmup_steps: 100 |
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eval_steps: 200 |
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eval_table_size: |
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eval_table_max_new_tokens: 128 |
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# max_steps: 500 |
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saves_per_epoch: 1 |
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debug: |
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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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bos_token: "<|im_start|>" |
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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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# rainbowfish-v9-adapter |
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This model is a fine-tuned version of [andysalerno/mistral-sft-v3](https://huggingface.co/andysalerno/mistral-sft-v3) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6456 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 4 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 16 |
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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: 100 |
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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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| 0.6535 | 0.18 | 200 | 0.6840 | |
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| 0.69 | 0.37 | 400 | 0.6711 | |
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| 0.6649 | 0.55 | 600 | 0.6641 | |
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| 0.6959 | 0.74 | 800 | 0.6590 | |
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| 0.717 | 0.92 | 1000 | 0.6547 | |
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| 0.5243 | 1.11 | 1200 | 0.6540 | |
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| 0.6285 | 1.29 | 1400 | 0.6523 | |
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| 0.6219 | 1.47 | 1600 | 0.6504 | |
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| 0.6334 | 1.66 | 1800 | 0.6486 | |
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| 0.6627 | 1.84 | 2000 | 0.6466 | |
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| 0.6319 | 2.03 | 2200 | 0.6460 | |
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| 0.6081 | 2.21 | 2400 | 0.6466 | |
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| 0.5721 | 2.4 | 2600 | 0.6459 | |
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| 0.5794 | 2.58 | 2800 | 0.6447 | |
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| 0.721 | 2.76 | 3000 | 0.6443 | |
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| 0.5825 | 2.95 | 3200 | 0.6436 | |
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| 0.5921 | 3.13 | 3400 | 0.6457 | |
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| 0.5224 | 3.32 | 3600 | 0.6461 | |
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| 0.5466 | 3.5 | 3800 | 0.6456 | |
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| 0.5972 | 3.69 | 4000 | 0.6460 | |
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| 0.5999 | 3.87 | 4200 | 0.6456 | |
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### Framework versions |
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- PEFT 0.8.2 |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.0 |
