lBober's picture
lBober/my-model-Bertin-Area
eb4dc9d verified
|
raw
history blame
3.35 kB
metadata
license: cc-by-4.0
base_model: bertin-project/bertin-roberta-base-spanish
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: my-model-Bertin-Area
    results: []

my-model-Bertin-Area

This model is a fine-tuned version of bertin-project/bertin-roberta-base-spanish on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 3.1711
  • Accuracy: 0.4903
  • F1: 0.4767
  • Precision: 0.5366
  • Recall: 0.4903

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: 30
  • eval_batch_size: 5
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
1.8349 1.0 25 1.7703 0.3032 0.2608 0.2991 0.3032
1.7709 2.0 50 1.7153 0.3355 0.2347 0.2079 0.3355
1.7315 3.0 75 1.6515 0.3613 0.2934 0.2937 0.3613
1.596 4.0 100 1.6332 0.3871 0.3405 0.3123 0.3871
1.3388 5.0 125 1.6449 0.4065 0.3298 0.2900 0.4065
1.0783 6.0 150 1.5722 0.4581 0.3797 0.3760 0.4581
0.8663 7.0 175 1.6593 0.3935 0.3563 0.3490 0.3935
0.6118 8.0 200 1.9177 0.4581 0.4481 0.4658 0.4581
0.4206 9.0 225 2.2944 0.4065 0.3920 0.4286 0.4065
0.3375 10.0 250 2.2870 0.4387 0.4359 0.4889 0.4387
0.2334 11.0 275 2.4912 0.4065 0.4015 0.4546 0.4065
0.1618 12.0 300 2.5429 0.4710 0.4499 0.5204 0.4710
0.1238 13.0 325 2.7109 0.4710 0.4458 0.5135 0.4710
0.0906 14.0 350 2.8377 0.4774 0.4594 0.5092 0.4774
0.071 15.0 375 3.0123 0.4839 0.4656 0.5461 0.4839
0.0498 16.0 400 3.0204 0.4710 0.4517 0.4959 0.4710
0.0416 17.0 425 3.0939 0.4839 0.4622 0.5107 0.4839
0.0281 18.0 450 3.0979 0.4903 0.4793 0.5281 0.4903
0.0226 19.0 475 3.1622 0.4839 0.4708 0.5202 0.4839
0.0185 20.0 500 3.1711 0.4903 0.4767 0.5366 0.4903

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1