| | --- |
| | library_name: peft |
| | base_model: ProsusAI/finbert |
| | tags: |
| | - base_model:adapter:ProsusAI/finbert |
| | - lora |
| | - transformers |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: finbert_lora |
| | 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. --> |
| |
|
| | # finbert_lora |
| | |
| | This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3124 |
| | - Accuracy: 0.8630 |
| | - Precision: 0.8480 |
| | - Recall: 0.8562 |
| | - F1: 0.8521 |
| | |
| | ## 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: 0.0002 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 2 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | 0.3374 | 1.0 | 5013 | 0.3304 | 0.8518 | 0.8172 | 0.8739 | 0.8446 | |
| | | 0.3287 | 2.0 | 10026 | 0.3101 | 0.8633 | 0.8458 | 0.8603 | 0.8530 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.18.0 |
| | - Transformers 4.57.3 |
| | - Pytorch 2.9.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.2 |
