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--- |
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base_model: unsloth/Mistral-Nemo-Base-2407 |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- axolotl |
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- generated_from_trainer |
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model-index: |
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- name: adventure-nemo-ws |
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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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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# python -m axolotl.cli.preprocess adventure-nemo.yml |
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# accelerate launch -m axolotl.cli.train adventure-nemo.yml |
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# python -m axolotl.cli.merge_lora adventure-nemo.yml |
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base_model: unsloth/Mistral-Nemo-Base-2407 |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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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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sequence_len: 8192 # 99% vram |
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bf16: auto |
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fp16: |
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tf32: false |
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flash_attention: true |
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special_tokens: |
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# Data |
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dataset_prepared_path: last_run_prepared |
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datasets: |
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- path: ColumbidAI/adventure-8k |
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type: completion |
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warmup_steps: 10 |
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shuffle_merged_datasets: true |
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save_safetensors: true |
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saves_per_epoch: 4 |
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save_total_limit: 2 |
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# WandB |
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wandb_project: Nemo-A |
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wandb_entity: |
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# Iterations |
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num_epochs: 1 |
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# Output |
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output_dir: ./adventure-command-r-workspace |
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hub_model_id: ToastyPigeon/adventure-nemo-ws |
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hub_strategy: "all_checkpoints" |
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# Sampling |
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sample_packing: true |
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pad_to_sequence_len: true |
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# Batching |
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gradient_accumulation_steps: 1 |
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micro_batch_size: 4 |
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gradient_checkpointing: 'unsloth' |
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gradient_checkpointing_kwargs: |
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use_reentrant: true |
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#unsloth_cross_entropy_loss: true |
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#unsloth_lora_mlp: true |
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#unsloth_lora_qkv: true |
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#unsloth_lora_o: true |
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# Evaluation |
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val_set_size: 0.005 |
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evals_per_epoch: 5 |
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eval_table_size: |
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eval_max_new_tokens: 256 |
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eval_sample_packing: false |
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eval_batch_size: 1 |
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# LoRA |
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adapter: qlora |
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lora_model_dir: |
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lora_r: 64 |
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lora_alpha: 32 |
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lora_dropout: 0.125 |
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lora_target_linear: |
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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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# Optimizer |
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optimizer: paged_adamw_8bit # adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.00025 |
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lr_scheduler: cosine_with_min_lr |
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lr_scheduler_kwargs: |
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min_lr: 0.000025 |
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weight_decay: 0.01 |
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max_grad_norm: 20.0 |
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# Misc |
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train_on_inputs: false |
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group_by_length: false |
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early_stopping_patience: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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debug: |
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#deepspeed: /workspace/axolotl/deepspeed_configs/zero3.json # previously blank |
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fsdp: |
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fsdp_config: |
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plugins: |
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- axolotl.integrations.liger.LigerPlugin |
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liger_rope: true |
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liger_rms_norm: true |
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liger_swiglu: true |
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liger_fused_linear_cross_entropy: true |
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``` |
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</details><br> |
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# adventure-nemo-ws |
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This model is a fine-tuned version of [unsloth/Mistral-Nemo-Base-2407](https://huggingface.co/unsloth/Mistral-Nemo-Base-2407) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1587 |
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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: 0.00025 |
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- train_batch_size: 4 |
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- eval_batch_size: 1 |
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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_with_min_lr |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.9422 | 0.0011 | 1 | 2.3948 | |
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| 1.8427 | 0.2011 | 189 | 2.2440 | |
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| 1.6786 | 0.4021 | 378 | 2.2143 | |
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| 1.9847 | 0.6032 | 567 | 2.1799 | |
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| 1.8358 | 0.8043 | 756 | 2.1587 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
