| --- |
| library_name: peft |
| base_model: TinyPixel/small-llama2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: debug_test |
| 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. --> |
|
|
| # debug_test |
| |
| This model is a fine-tuned version of [TinyPixel/small-llama2](https://huggingface.co/TinyPixel/small-llama2) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7894 |
| - Accuracy: 0.4982 |
| - Precision: 0.3939 |
| - Recall: 0.7114 |
| - F1: 0.5071 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 4 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 64 |
| - total_eval_batch_size: 32 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.8214 | 1.0 | 5 | 0.7894 | 0.4982 | 0.3939 | 0.7114 | 0.5071 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.13.2 |
| - Transformers 4.46.0 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
