| --- |
| library_name: peft |
| license: apache-2.0 |
| base_model: HuggingFaceTB/SmolLM2-360M |
| tags: |
| - base_model:adapter:HuggingFaceTB/SmolLM2-360M |
| - lora |
| - transformers |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| model-index: |
| - name: HuggingFaceTB_SmolLM2-360M_StereoDetect_Model |
| 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. --> |
|
|
| # HuggingFaceTB_SmolLM2-360M_StereoDetect_Model |
| |
| This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-360M](https://huggingface.co/HuggingFaceTB/SmolLM2-360M) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3245 |
| - Accuracy: 0.8906 |
| - Balanced Accuracy: 0.8935 |
| - F1 Weighted: 0.8905 |
| - F1 Macro: 0.8914 |
| - Precision: 0.8919 |
| - Recall: 0.8906 |
| |
| ## 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: 0.0001 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Balanced Accuracy | F1 Weighted | F1 Macro | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:-----------:|:--------:|:---------:|:------:| |
| | 0.7655 | 1.0 | 760 | 0.3760 | 0.8399 | 0.8424 | 0.8371 | 0.8382 | 0.8484 | 0.8399 | |
| | 0.2651 | 2.0 | 1520 | 0.2842 | 0.8825 | 0.8840 | 0.8815 | 0.8825 | 0.8890 | 0.8825 | |
| | 0.1856 | 3.0 | 2280 | 0.2940 | 0.8802 | 0.8835 | 0.8795 | 0.8806 | 0.8824 | 0.8802 | |
| | 0.1307 | 4.0 | 3040 | 0.3245 | 0.8906 | 0.8935 | 0.8905 | 0.8914 | 0.8919 | 0.8906 | |
| | 0.0938 | 5.0 | 3800 | 0.3328 | 0.8871 | 0.8898 | 0.8871 | 0.8877 | 0.8875 | 0.8871 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.19.1 |
| - Transformers 4.51.3 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 4.8.5 |
| - Tokenizers 0.21.4 |
