| | --- |
| | license: apache-2.0 |
| | library_name: peft |
| | tags: |
| | - trl |
| | - sft |
| | - unsloth |
| | - generated_from_trainer |
| | base_model: unsloth/mistral-7b-instruct-v0.2-bnb-4bit |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: mistral_numericnlg_FV |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # mistral_numericnlg_FV |
| |
|
| | This model is a fine-tuned version of [unsloth/mistral-7b-instruct-v0.2-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-instruct-v0.2-bnb-4bit) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.2038 |
| | - Rouge1: 0.6650 |
| | - Rougel: 0.5559 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 1e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 1 |
| | - seed: 3407 |
| | - gradient_accumulation_steps: 16 |
| | - total_train_batch_size: 64 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 5 |
| | - num_epochs: 6 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rougel | |
| | |:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
| | | 1.3723 | 0.9446 | 16 | 1.3128 | 0.6406 | 0.5251 | |
| | | 1.2226 | 1.9483 | 33 | 1.2305 | 0.6603 | 0.5562 | |
| | | 1.1781 | 2.9520 | 50 | 1.2129 | 0.6658 | 0.5556 | |
| | | 1.2057 | 3.9557 | 67 | 1.2062 | 0.6659 | 0.5560 | |
| | | 1.215 | 4.9594 | 84 | 1.2040 | 0.6656 | 0.5551 | |
| | | 1.1676 | 5.6679 | 96 | 1.2038 | 0.6650 | 0.5559 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.11.1 |
| | - Transformers 4.41.2 |
| | - Pytorch 2.2.0 |
| | - Datasets 2.16.0 |
| | - Tokenizers 0.19.1 |
