| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: gpt2 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: sentimental-gpt |
| | 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. --> |
| |
|
| | # sentimental-gpt |
| |
|
| | 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: 0.5305 |
| | - Accuracy: 0.7985 |
| |
|
| | ## 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 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 16 |
| | - 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 |
| | - lr_scheduler_warmup_steps: 500 |
| | - num_epochs: 3 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 0.7515 | 0.2910 | 500 | 0.6684 | 0.7187 | |
| | | 0.6015 | 0.5821 | 1000 | 0.5922 | 0.7609 | |
| | | 0.5758 | 0.8731 | 1500 | 0.5355 | 0.7804 | |
| | | 0.5301 | 1.1641 | 2000 | 0.5441 | 0.7801 | |
| | | 0.4545 | 1.4552 | 2500 | 0.5318 | 0.7917 | |
| | | 0.5103 | 1.7462 | 3000 | 0.5479 | 0.7796 | |
| | | 0.4495 | 2.0373 | 3500 | 0.5212 | 0.7906 | |
| | | 0.4506 | 2.3283 | 4000 | 0.5282 | 0.7963 | |
| | | 0.4271 | 2.6193 | 4500 | 0.5305 | 0.7985 | |
| | | 0.44 | 2.9104 | 5000 | 0.5335 | 0.7971 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.49.0 |
| | - Pytorch 2.0.0+cu118 |
| | - Datasets 3.3.1 |
| | - Tokenizers 0.21.0 |
| |
|
