| | --- |
| | license: mit |
| | library_name: peft |
| | tags: |
| | - generated_from_trainer |
| | base_model: openai-community/gpt2 |
| | datasets: |
| | - financial_phrasebank |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: gpt2-sentiment_analysis |
| | 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-sentiment_analysis |
| | |
| | This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the financial_phrasebank dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6571 |
| | - Accuracy: {'accuracy': 0.8239339752407153} |
| |
|
| | ## 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: 0.0006 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------------------------------:| |
| | | No log | 0.9981 | 257 | 0.4654 | {'accuracy': 0.8239339752407153} | |
| | | 0.6288 | 2.0 | 515 | 0.4266 | {'accuracy': 0.8266850068775791} | |
| | | 0.6288 | 2.9981 | 772 | 0.4558 | {'accuracy': 0.8225584594222833} | |
| | | 0.3201 | 4.0 | 1030 | 0.4550 | {'accuracy': 0.811554332874828} | |
| | | 0.3201 | 4.9981 | 1287 | 0.4223 | {'accuracy': 0.8294360385144429} | |
| | | 0.2464 | 6.0 | 1545 | 0.4637 | {'accuracy': 0.8335625859697386} | |
| | | 0.2464 | 6.9981 | 1802 | 0.5243 | {'accuracy': 0.8184319119669876} | |
| | | 0.1859 | 8.0 | 2060 | 0.5482 | {'accuracy': 0.8335625859697386} | |
| | | 0.1859 | 8.9981 | 2317 | 0.6443 | {'accuracy': 0.8335625859697386} | |
| | | 0.1381 | 9.9806 | 2570 | 0.6571 | {'accuracy': 0.8239339752407153} | |
| | |
| | |
| | ### Framework versions |
| | |
| | - PEFT 0.11.1 |
| | - Transformers 4.41.0 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.1 |
| | - Tokenizers 0.19.1 |
