XLMR-ENIS-finetuned-ner
This model is a fine-tuned version of vesteinn/XLMR-ENIS on the mim_gold_ner dataset. It achieves the following results on the evaluation set:
- Loss: 0.0827
- Precision: 0.9002
- Recall: 0.896
- F1: 0.8981
- Accuracy: 0.9844
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0567 | 1.0 | 2904 | 0.1081 | 0.8486 | 0.8140 | 0.8309 | 0.9796 |
0.0302 | 2.0 | 5808 | 0.0906 | 0.8620 | 0.8298 | 0.8456 | 0.9818 |
0.0197 | 3.0 | 8712 | 0.0948 | 0.8691 | 0.8447 | 0.8567 | 0.9826 |
Framework versions
- Transformers 4.11.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
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Evaluation results
- Precision on mim_gold_nerself-reported0.900
- Recall on mim_gold_nerself-reported0.896
- F1 on mim_gold_nerself-reported0.898
- Accuracy on mim_gold_nerself-reported0.984