GPT2-705M

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 5.5538

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: 0.00025
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
9.7407 0.57 1 9.7354
8.0949 1.71 3 9.2987
8.037 2.86 5 7.9942
8.4143 4.0 7 8.3825
7.7196 4.57 8 8.7978
7.2632 5.71 10 7.6261
6.9715 6.86 12 7.4135
6.4835 8.0 14 8.2776
7.1529 8.57 15 7.0085
6.1255 9.71 17 6.8228
5.9176 10.86 19 6.5603
5.5785 12.0 21 6.3862
5.4833 12.57 22 6.3011
5.1483 13.71 24 6.0480
4.9268 14.86 26 6.0532
4.6602 16.0 28 5.7750
4.5647 16.57 29 5.7046
4.3202 17.71 31 5.5333
4.1764 18.86 33 5.5809
4.1745 20.0 35 5.4089
4.0056 20.57 36 5.3978
3.8024 21.71 38 5.4085
3.5845 22.86 40 5.3279
3.4378 24.0 42 5.3881
3.3361 24.57 43 5.2754
3.2585 25.71 45 5.2913
3.168 26.86 47 5.4232
2.9045 28.0 49 5.5044
2.8709 28.57 50 5.5538

Framework versions

  • Transformers 4.39.1
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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Evaluation results