metadata
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentimental-gpt
results: []
sentimental-gpt
This model is a fine-tuned version of 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