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Bert_TPF_v10

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bert
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metadata
library_name: transformers
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
  - generated_from_trainer
model-index:
  - name: Bert_TPF_v10
    results: []

Bert_TPF_v10

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Accuracy@en: 0.8315
  • F1@en: 0.8323
  • Precision@en: 0.8373
  • Recall@en: 0.8368
  • Loss@en: 0.6173
  • Loss: 0.6173

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 20

Training results

Training Loss Epoch Step Accuracy@en F1@en Precision@en Recall@en Loss@en Validation Loss
3.2405 1.0 552 0.2037 0.1306 0.1465 0.2065 2.5934 2.5934
2.3891 2.0 1104 0.2992 0.2349 0.2586 0.3058 2.0876 2.0876
2.0117 3.0 1656 0.3765 0.3448 0.3683 0.3839 1.8638 1.8638
1.7804 4.0 2208 0.4619 0.4287 0.4433 0.4705 1.6337 1.6337
1.4913 5.0 2760 0.5228 0.4905 0.5357 0.5306 1.3950 1.3950
1.2177 6.0 3312 0.5696 0.5529 0.6054 0.5773 1.2562 1.2562
1.0274 7.0 3864 0.6278 0.6086 0.6598 0.6360 1.0466 1.0466
0.8372 8.0 4416 0.7050 0.7007 0.7254 0.7104 0.8734 0.8734
0.67 9.0 4968 0.7407 0.7373 0.7510 0.7463 0.8112 0.8112
0.5259 10.0 5520 0.8 0.7999 0.8069 0.8050 0.6594 0.6594
0.4333 11.0 6072 0.8095 0.8056 0.8219 0.8159 0.6305 0.6305
0.3503 12.0 6624 0.8019 0.7985 0.8132 0.8074 0.6698 0.6698
0.2961 13.0 7176 0.8315 0.8323 0.8373 0.8368 0.6173 0.6173
0.2441 14.0 7728 0.8450 0.8459 0.8482 0.8493 0.6287 0.6287
0.2078 15.0 8280 0.8471 0.8477 0.8508 0.8511 0.6280 0.6280
0.1857 16.0 8832 0.8463 0.8470 0.8513 0.8510 0.6293 0.6293
0.164 17.0 9384 0.8471 0.8480 0.8510 0.8512 0.6371 0.6371
0.1467 18.0 9936 0.8489 0.8497 0.8536 0.8532 0.6410 0.6410
0.1409 19.0 10488 0.8489 0.8496 0.8535 0.8528 0.6396 0.6396
0.1378 20.0 11040 0.8497 0.8505 0.8543 0.8537 0.6395 0.6395

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.5.0+cu121
  • Datasets 3.0.2
  • Tokenizers 0.19.1