deberta-v3-large-finetuned-ner-10epochs
This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0776
- Precision: 0.9247
- Recall: 0.9531
- F1: 0.9387
- Accuracy: 0.9890
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0415 | 1.0 | 2261 | 0.0479 | 0.8894 | 0.9572 | 0.9220 | 0.9861 |
0.039 | 2.0 | 4522 | 0.0415 | 0.9051 | 0.9498 | 0.9269 | 0.9871 |
0.0304 | 3.0 | 6783 | 0.0390 | 0.9086 | 0.9579 | 0.9326 | 0.9883 |
0.0275 | 4.0 | 9044 | 0.0383 | 0.9146 | 0.9528 | 0.9333 | 0.9887 |
0.0224 | 5.0 | 11305 | 0.0421 | 0.9122 | 0.9583 | 0.9346 | 0.9884 |
0.0172 | 6.0 | 13566 | 0.0459 | 0.9204 | 0.9568 | 0.9382 | 0.9890 |
0.0122 | 7.0 | 15827 | 0.0561 | 0.9273 | 0.9429 | 0.9350 | 0.9885 |
0.0096 | 8.0 | 18088 | 0.0616 | 0.9223 | 0.9568 | 0.9393 | 0.9891 |
0.0051 | 9.0 | 20349 | 0.0718 | 0.9240 | 0.9568 | 0.9401 | 0.9890 |
0.0034 | 10.0 | 22610 | 0.0776 | 0.9247 | 0.9531 | 0.9387 | 0.9890 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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