gpt2-finetuned / README.md
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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - bleu
base_model: openai-community/gpt2
model-index:
  - name: gpt2-finetuned
    results: []

gpt2-finetuned

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: 1.6944
  • Bleu: 0.0294
  • Bertscore Precision: 0.1536
  • Bertscore Recall: 0.1658
  • Bertscore F1: 0.1592

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: 20

Training results

Training Loss Epoch Step Validation Loss Bleu Bertscore Precision Bertscore Recall Bertscore F1
4.716 1.0 5750 3.4413 0.0112 0.1417 0.1575 0.1489
4.5916 2.0 11500 3.2372 0.0119 0.1424 0.1583 0.1496
4.325 3.0 17250 3.0534 0.0128 0.1430 0.1587 0.1501
4.1626 4.0 23000 2.9061 0.0136 0.1433 0.1592 0.1505
4.0255 5.0 28750 2.7554 0.0148 0.1438 0.1599 0.1511
3.862 6.0 34500 2.6185 0.0346 0.1446 0.1605 0.1518
3.7367 7.0 40250 2.4945 0.0286 0.1456 0.1611 0.1527
3.7907 8.0 46000 2.3799 0.0401 0.1488 0.1617 0.1548
3.5181 9.0 51750 2.2704 0.0607 0.1490 0.1623 0.1551
3.3377 10.0 57500 2.1710 0.0804 0.1498 0.1627 0.1558
3.294 11.0 63250 2.0876 0.0221 0.1512 0.1633 0.1568
3.1612 12.0 69000 2.0004 0.0234 0.1516 0.1637 0.1572
3.1257 13.0 74750 1.9356 0.0244 0.1518 0.1642 0.1575
3.1347 14.0 80500 1.8769 0.0257 0.1525 0.1646 0.1581
2.8094 15.0 86250 1.8210 0.0268 0.1527 0.1649 0.1584
2.8519 16.0 92000 1.7776 0.0275 0.1530 0.1652 0.1587
2.782 17.0 97750 1.7438 0.0282 0.1532 0.1654 0.1589
2.9097 18.0 103500 1.7183 0.0289 0.1535 0.1657 0.1591
2.881 19.0 109250 1.6999 0.0293 0.1536 0.1658 0.1592
2.6302 20.0 115000 1.6944 0.0294 0.1536 0.1658 0.1592

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1