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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: 1.3b-all-2-epoch-v1-after-book
    results: []

1.3b-all-2-epoch-v1-after-book

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9482
  • Accuracy: 0.0640

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: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 32
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 2.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.17 0.07 1 2.0547 0.0621
2.1814 0.13 2 2.0547 0.0621
2.0963 0.2 3 2.0234 0.0625
2.1383 0.27 4 2.0195 0.0625
2.1625 0.33 5 2.0195 0.0625
2.1808 0.4 6 2.0156 0.0624
2.1587 0.47 7 2.0176 0.0626
2.0847 0.53 8 2.0137 0.0627
2.0336 0.6 9 2.0137 0.0627
2.1777 0.67 10 2.0059 0.0629
2.2034 0.73 11 2.0 0.0630
2.1665 0.8 12 1.9941 0.0628
2.0352 0.87 13 1.9883 0.0629
2.1263 0.93 14 1.9834 0.0628
2.1282 1.0 15 1.9785 0.0632
1.7159 1.07 16 1.9766 0.0633
1.8346 1.13 17 1.9775 0.0635
1.7183 1.2 18 1.9824 0.0634
1.6086 1.27 19 1.9883 0.0635
1.6497 1.33 20 1.9893 0.0634
1.6267 1.4 21 1.9854 0.0637
1.5962 1.47 22 1.9766 0.0637
1.5168 1.53 23 1.9697 0.0637
1.6213 1.6 24 1.9619 0.0637
1.4789 1.67 25 1.9580 0.0638
1.6796 1.73 26 1.9551 0.0638
1.5964 1.8 27 1.9531 0.0638
1.787 1.87 28 1.9512 0.0639
1.6536 1.93 29 1.9492 0.0640
1.7178 2.0 30 1.9482 0.0640

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.3.2
  • Tokenizers 0.12.1