my_xlm-roberta-large-finetuned-conlljob03
This model is a fine-tuned version of xlm-roberta-large on the conll2003job dataset. It achieves the following results on the evaluation set:
- Loss: 0.0364
- Precision: 0.9593
- Recall: 0.9670
- F1: 0.9631
- Accuracy: 0.9933
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: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.1596 | 1.0 | 896 | 0.0385 | 0.9393 | 0.9556 | 0.9474 | 0.9915 |
0.0298 | 2.0 | 1792 | 0.0377 | 0.9532 | 0.9594 | 0.9563 | 0.9920 |
0.0158 | 3.0 | 2688 | 0.0339 | 0.9579 | 0.9658 | 0.9619 | 0.9931 |
0.0087 | 4.0 | 3584 | 0.0364 | 0.9593 | 0.9670 | 0.9631 | 0.9933 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Base model
FacebookAI/xlm-roberta-largeEvaluation results
- Precision on conll2003jobvalidation set self-reported0.959
- Recall on conll2003jobvalidation set self-reported0.967
- F1 on conll2003jobvalidation set self-reported0.963
- Accuracy on conll2003jobvalidation set self-reported0.993