generated_from_trainer

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ES-ENG-xlm-roberta-sentiment

This model is a fine-tuned version of xlm-roberta-base on a Custom dataset.

The best model (stopped after 20 epochs) achieves the following results on the evaluation set:

Intended uses & limitations

Note that commercial use with this model is prohibited.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
1.1099 1.0 208 1.0718 0.3968 0.3851 0.4857 0.3968
1.0057 2.0 416 0.8926 0.5492 0.5080 0.5639 0.5492
0.8988 3.0 624 0.8384 0.5883 0.5792 0.5789 0.5883
0.8606 4.0 832 0.8209 0.6168 0.6086 0.6086 0.6168
0.8338 5.0 1040 0.8006 0.6120 0.6068 0.6046 0.6120
0.8081 6.0 1248 0.8074 0.6026 0.5935 0.5966 0.6026
0.7872 7.0 1456 0.7786 0.6194 0.6149 0.6127 0.6194
0.7624 8.0 1664 0.7783 0.6379 0.6277 0.6342 0.6379
0.7446 9.0 1872 0.7643 0.6366 0.6287 0.6314 0.6366
0.7274 10.0 2080 0.7846 0.6395 0.6297 0.6351 0.6395
0.7116 11.0 2288 0.7465 0.6495 0.6425 0.6462 0.6495
0.6998 12.0 2496 0.7599 0.6537 0.6474 0.6494 0.6537
0.6852 13.0 2704 0.7651 0.6515 0.6443 0.6465 0.6515
0.6726 14.0 2912 0.7571 0.6576 0.6536 0.6530 0.6576
0.6665 15.0 3120 0.7597 0.6557 0.6506 0.6514 0.6557
0.6541 16.0 3328 0.7590 0.6615 0.6584 0.6576 0.6615
0.6513 17.0 3536 0.7617 0.6599 0.6544 0.6555 0.6599
0.6392 18.0 3744 0.7740 0.6628 0.6585 0.6582 0.6628
0.6369 19.0 3952 0.7666 0.6631 0.6588 0.6585 0.6631
0.6268 20.0 4160 0.7743 0.6702 0.6672 0.6664 0.6702
0.62 21.0 4368 0.7712 0.6680 0.6638 0.6638 0.6680
0.619 22.0 4576 0.7720 0.6689 0.6656 0.6649 0.6689
0.6074 23.0 4784 0.7729 0.6663 0.6630 0.6621 0.6663

Framework versions