distilgpt2-finetuned

This model is a fine-tuned version of distilgpt2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.6391

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
4.0748 0.0436 50 3.8923
3.8414 0.0871 100 3.8125
3.8957 0.1307 150 3.7769
3.8723 0.1743 200 3.7545
4.0205 0.2179 250 3.7336
3.7175 0.2614 300 3.7282
3.7778 0.3050 350 3.7111
3.7763 0.3486 400 3.6994
3.8142 0.3922 450 3.6945
3.7654 0.4357 500 3.6831
3.9636 0.4793 550 3.6773
3.703 0.5229 600 3.6692
3.6114 0.5664 650 3.6647
3.6269 0.6100 700 3.6591
3.693 0.6536 750 3.6564
3.7969 0.6972 800 3.6529
3.6011 0.7407 850 3.6491
3.4943 0.7843 900 3.6466
3.7543 0.8279 950 3.6440
3.861 0.8715 1000 3.6406
3.5354 0.9150 1050 3.6401
3.6661 0.9586 1100 3.6396

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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