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bertin-roberta-base-spanish-finetuned-recores3

This model is a fine-tuned version of bertin-project/bertin-roberta-base-spanish on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 6.0975
  • Accuracy: 0.3884

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: 2e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 3000
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.6095 1.0 524 1.6094 0.2342
1.607 2.0 1048 1.5612 0.3058
1.4059 3.0 1572 1.6292 0.3361
0.7047 4.0 2096 2.5111 0.4132
0.2671 5.0 2620 3.2399 0.3499
0.1065 6.0 3144 5.1217 0.3444
0.0397 7.0 3668 4.3270 0.3691
0.0162 8.0 4192 5.1796 0.3719
0.0096 9.0 4716 5.2161 0.3994
0.0118 10.0 5240 4.9225 0.3719
0.0015 11.0 5764 5.0544 0.3829
0.0091 12.0 6288 5.7731 0.3884
0.0052 13.0 6812 4.1606 0.3939
0.0138 14.0 7336 6.2725 0.3857
0.0027 15.0 7860 6.2274 0.3857
0.0003 16.0 8384 6.0935 0.4022
0.0002 17.0 8908 5.7650 0.3994
0.0 18.0 9432 6.3595 0.4215
0.0 19.0 9956 5.8934 0.3747
0.0001 20.0 10480 6.0571 0.3884
0.0 21.0 11004 6.0718 0.3884
0.0 22.0 11528 6.0844 0.3884
0.0 23.0 12052 6.0930 0.3884
0.0 24.0 12576 6.0966 0.3884
0.0 25.0 13100 6.0975 0.3884

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1
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