gpt2-finetuned-mcqa
This model is a fine-tuned version of openai-community/gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4696
- Bertscore Precision: 0.1390
- Bertscore Recall: 0.1471
- Bertscore F1: 0.1428
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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 | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|---|---|---|---|---|---|---|
| 4.6412 | 1.0000 | 11719 | 2.9435 | 0.1223 | 0.1435 | 0.1316 |
| 4.4659 | 2.0 | 23439 | 2.8198 | 0.1268 | 0.1445 | 0.1346 |
| 4.1443 | 3.0000 | 35158 | 2.7298 | 0.1326 | 0.1452 | 0.1384 |
| 4.1037 | 4.0 | 46878 | 2.6608 | 0.1348 | 0.1457 | 0.1399 |
| 4.0107 | 5.0000 | 58597 | 2.5980 | 0.1338 | 0.1462 | 0.1395 |
| 4.0216 | 6.0 | 70317 | 2.5494 | 0.1353 | 0.1463 | 0.1404 |
| 3.5677 | 7.0000 | 82036 | 2.5156 | 0.1371 | 0.1466 | 0.1415 |
| 3.619 | 8.0 | 93756 | 2.4859 | 0.1376 | 0.1468 | 0.1419 |
| 3.5389 | 9.0000 | 105475 | 2.4735 | 0.1391 | 0.1470 | 0.1429 |
| 3.713 | 9.9996 | 117190 | 2.4696 | 0.1390 | 0.1471 | 0.1428 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1