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test5_balanced_60ep

This model is a fine-tuned version of ibaucells/RoBERTa-ca-CaWikiTC on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8209

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: 10
  • eval_batch_size: 10
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 60

Training results

Training Loss Epoch Step Validation Loss
2.8299 1.0 63 2.8361
2.8512 2.0 126 2.8253
2.8118 3.0 189 2.8376
2.7238 4.0 252 2.7157
2.5914 5.0 315 2.6045
2.5527 6.0 378 2.5580
2.4197 7.0 441 2.6009
2.2561 8.0 504 2.3989
1.9213 9.0 567 2.2129
1.8147 10.0 630 2.1155
1.4336 11.0 693 2.0509
1.2948 12.0 756 1.8276
0.9833 13.0 819 1.8245
0.8577 14.0 882 1.7360
0.665 15.0 945 1.8072
0.5397 16.0 1008 1.8583
0.2861 17.0 1071 1.9073
0.3394 18.0 1134 2.0320
0.2941 19.0 1197 2.1608
0.1868 20.0 1260 2.1440
0.175 21.0 1323 2.2099
0.3357 22.0 1386 2.3903
0.1311 23.0 1449 2.4006
0.103 24.0 1512 2.4874
0.1323 25.0 1575 2.5191
0.0928 26.0 1638 2.3582
0.0872 27.0 1701 2.4494
0.1271 28.0 1764 2.5821
0.1796 29.0 1827 2.6190
0.0479 30.0 1890 2.5549
0.0197 31.0 1953 2.8739
0.0222 32.0 2016 2.7927
0.019 33.0 2079 2.8467
0.0946 34.0 2142 2.9086
0.0084 35.0 2205 2.7976
0.0539 36.0 2268 2.8300
0.0553 37.0 2331 2.9293
0.0124 38.0 2394 3.0047
0.0447 39.0 2457 2.9724
0.0363 40.0 2520 2.9775
0.0056 41.0 2583 2.9972
0.0072 42.0 2646 3.0162
0.0091 43.0 2709 3.0348
0.031 44.0 2772 3.0490
0.0091 45.0 2835 3.0648
0.029 46.0 2898 3.0730
0.0076 47.0 2961 3.0866
0.0115 48.0 3024 3.0979
0.0047 49.0 3087 3.1102
0.0079 50.0 3150 3.1242
0.0039 51.0 3213 3.1299
0.0043 52.0 3276 3.1386
0.0322 53.0 3339 3.1478
0.0041 54.0 3402 3.1478
0.0289 55.0 3465 3.1570
0.0038 56.0 3528 3.1661
0.004 57.0 3591 3.1546
0.0037 58.0 3654 3.1575
0.0069 59.0 3717 3.1587
0.0135 60.0 3780 3.1626

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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