| base_model: gpt2 | |
| library_name: peft | |
| license: mit | |
| metrics: | |
| - accuracy | |
| - f1 | |
| - precision | |
| - recall | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: gpt2-sst2-sentiment-classifier-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. --> | |
| # gpt2-sst2-sentiment-classifier-lora | |
| This model is a fine-tuned version of [gpt2](https://huggingface.co./gpt2) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.2636 | |
| - Accuracy: 0.9083 | |
| - F1: 0.9111 | |
| - Precision: 0.8991 | |
| - Recall: 0.9234 | |
| ## 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: 5e-05 | |
| - train_batch_size: 16 | |
| - eval_batch_size: 64 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 500 | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| | |
| | 0.3138 | 1.0 | 4210 | 0.2550 | 0.9014 | 0.9034 | 0.9013 | 0.9054 | | |
| | 0.2597 | 2.0 | 8420 | 0.2666 | 0.9014 | 0.9061 | 0.8792 | 0.9347 | | |
| | 0.2436 | 3.0 | 12630 | 0.2636 | 0.9083 | 0.9111 | 0.8991 | 0.9234 | | |
| ### Framework versions | |
| - PEFT 0.12.0 | |
| - Transformers 4.44.2 | |
| - Pytorch 2.4.1+cu121 | |
| - Datasets 3.0.0 | |
| - Tokenizers 0.19.1 |