--- base_model: dccuchile/bert-base-spanish-wwm-cased tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: FNST_trad_2a results: [] --- # FNST_trad_2a This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 4.0162 - Accuracy: 0.6525 - F1: 0.6433 ## 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: 1e-05 - train_batch_size: 6 - eval_batch_size: 6 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 78 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:------:|:---------------:|:--------:|:------:| | 1.1219 | 1.0 | 2000 | 1.0718 | 0.5383 | 0.4455 | | 0.9768 | 2.0 | 4000 | 0.9417 | 0.595 | 0.5797 | | 0.8945 | 3.0 | 6000 | 0.9033 | 0.6092 | 0.6039 | | 0.8746 | 4.0 | 8000 | 0.8784 | 0.6275 | 0.6224 | | 0.802 | 5.0 | 10000 | 0.8671 | 0.6367 | 0.6302 | | 0.7519 | 6.0 | 12000 | 0.8689 | 0.6375 | 0.6322 | | 0.7418 | 7.0 | 14000 | 0.8705 | 0.6383 | 0.6324 | | 0.7059 | 8.0 | 16000 | 0.8827 | 0.6408 | 0.6379 | | 0.669 | 9.0 | 18000 | 0.9116 | 0.635 | 0.6312 | | 0.6187 | 10.0 | 20000 | 0.9554 | 0.6483 | 0.6437 | | 0.5805 | 11.0 | 22000 | 0.9859 | 0.6383 | 0.6344 | | 0.5586 | 12.0 | 24000 | 0.9893 | 0.6425 | 0.6329 | | 0.4964 | 13.0 | 26000 | 1.0624 | 0.645 | 0.6348 | | 0.4637 | 14.0 | 28000 | 1.1429 | 0.6375 | 0.6298 | | 0.4146 | 15.0 | 30000 | 1.2550 | 0.635 | 0.6291 | | 0.3859 | 16.0 | 32000 | 1.2847 | 0.6425 | 0.6350 | | 0.3613 | 17.0 | 34000 | 1.4032 | 0.6442 | 0.6375 | | 0.3566 | 18.0 | 36000 | 1.5330 | 0.6442 | 0.6363 | | 0.3014 | 19.0 | 38000 | 1.6704 | 0.6458 | 0.6384 | | 0.3236 | 20.0 | 40000 | 1.8629 | 0.6442 | 0.6406 | | 0.3181 | 21.0 | 42000 | 1.9695 | 0.6375 | 0.6361 | | 0.258 | 22.0 | 44000 | 2.0728 | 0.6467 | 0.6365 | | 0.2174 | 23.0 | 46000 | 2.1817 | 0.6442 | 0.6336 | | 0.2373 | 24.0 | 48000 | 2.3151 | 0.6542 | 0.6461 | | 0.2237 | 25.0 | 50000 | 2.3966 | 0.6392 | 0.6311 | | 0.1968 | 26.0 | 52000 | 2.5837 | 0.6375 | 0.6304 | | 0.1952 | 27.0 | 54000 | 2.6898 | 0.635 | 0.6283 | | 0.1734 | 28.0 | 56000 | 2.7676 | 0.6525 | 0.6464 | | 0.1791 | 29.0 | 58000 | 2.8467 | 0.6408 | 0.6341 | | 0.1723 | 30.0 | 60000 | 2.9415 | 0.6483 | 0.6382 | | 0.1437 | 31.0 | 62000 | 2.9579 | 0.6467 | 0.6390 | | 0.1377 | 32.0 | 64000 | 3.0478 | 0.6492 | 0.6429 | | 0.125 | 33.0 | 66000 | 3.1053 | 0.6433 | 0.6333 | | 0.1142 | 34.0 | 68000 | 3.1841 | 0.6442 | 0.6371 | | 0.1064 | 35.0 | 70000 | 3.2318 | 0.6483 | 0.6414 | | 0.1083 | 36.0 | 72000 | 3.3547 | 0.6367 | 0.6271 | | 0.0729 | 37.0 | 74000 | 3.4056 | 0.6483 | 0.6393 | | 0.0805 | 38.0 | 76000 | 3.3959 | 0.6467 | 0.6396 | | 0.0809 | 39.0 | 78000 | 3.4675 | 0.6458 | 0.6390 | | 0.0792 | 40.0 | 80000 | 3.5613 | 0.6408 | 0.6370 | | 0.0735 | 41.0 | 82000 | 3.5786 | 0.6442 | 0.6367 | | 0.0753 | 42.0 | 84000 | 3.6967 | 0.6408 | 0.6320 | | 0.0661 | 43.0 | 86000 | 3.6580 | 0.6425 | 0.6380 | | 0.0566 | 44.0 | 88000 | 3.7266 | 0.6392 | 0.6320 | | 0.0617 | 45.0 | 90000 | 3.5621 | 0.6608 | 0.6543 | | 0.0535 | 46.0 | 92000 | 3.6820 | 0.6458 | 0.6350 | | 0.0593 | 47.0 | 94000 | 3.5833 | 0.6517 | 0.6438 | | 0.0666 | 48.0 | 96000 | 3.5367 | 0.6542 | 0.6465 | | 0.0589 | 49.0 | 98000 | 3.7562 | 0.6492 | 0.6438 | | 0.0504 | 50.0 | 100000 | 3.6989 | 0.6483 | 0.6372 | | 0.0414 | 51.0 | 102000 | 3.6851 | 0.6542 | 0.6472 | | 0.0454 | 52.0 | 104000 | 3.8027 | 0.6483 | 0.6436 | | 0.0421 | 53.0 | 106000 | 3.9190 | 0.6475 | 0.6415 | | 0.0422 | 54.0 | 108000 | 3.7929 | 0.6567 | 0.6478 | | 0.0476 | 55.0 | 110000 | 3.9425 | 0.6458 | 0.6387 | | 0.0539 | 56.0 | 112000 | 3.8677 | 0.6542 | 0.6477 | | 0.0471 | 57.0 | 114000 | 3.8409 | 0.6467 | 0.6390 | | 0.0466 | 58.0 | 116000 | 3.8810 | 0.6442 | 0.6394 | | 0.0241 | 59.0 | 118000 | 3.9288 | 0.645 | 0.6355 | | 0.0517 | 60.0 | 120000 | 3.9219 | 0.65 | 0.6433 | | 0.0373 | 61.0 | 122000 | 3.9035 | 0.6467 | 0.6406 | | 0.0354 | 62.0 | 124000 | 3.9745 | 0.6492 | 0.6453 | | 0.0412 | 63.0 | 126000 | 3.8600 | 0.6508 | 0.6436 | | 0.0347 | 64.0 | 128000 | 3.9549 | 0.6458 | 0.6369 | | 0.026 | 65.0 | 130000 | 4.0143 | 0.6492 | 0.6455 | | 0.0322 | 66.0 | 132000 | 3.9391 | 0.6583 | 0.6518 | | 0.0209 | 67.0 | 134000 | 3.9041 | 0.6583 | 0.6480 | | 0.0444 | 68.0 | 136000 | 4.0050 | 0.6517 | 0.6471 | | 0.0468 | 69.0 | 138000 | 3.9229 | 0.6508 | 0.6433 | | 0.0348 | 70.0 | 140000 | 4.0621 | 0.6483 | 0.6423 | | 0.0336 | 71.0 | 142000 | 3.9194 | 0.6542 | 0.6478 | | 0.0331 | 72.0 | 144000 | 3.9868 | 0.6517 | 0.6394 | | 0.0263 | 73.0 | 146000 | 3.9032 | 0.6467 | 0.6380 | | 0.0289 | 74.0 | 148000 | 4.0713 | 0.6417 | 0.6342 | | 0.0301 | 75.0 | 150000 | 4.0151 | 0.6433 | 0.6341 | | 0.0312 | 76.0 | 152000 | 3.9339 | 0.6533 | 0.6452 | | 0.0371 | 77.0 | 154000 | 3.9741 | 0.6542 | 0.6463 | | 0.0273 | 78.0 | 156000 | 4.0162 | 0.6525 | 0.6433 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1