RoBERTa-large-PM-M3-Voc-hf-finetuned-ner
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3493
- Precision: 0.6836
- Recall: 0.8494
- F1: 0.7575
- Accuracy: 0.9116
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: cosine
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 23 | 1.2145 | 0.1762 | 0.0340 | 0.0569 | 0.7236 |
No log | 2.0 | 46 | 0.8308 | 0.4435 | 0.3547 | 0.3942 | 0.7735 |
No log | 3.0 | 69 | 0.7051 | 0.4419 | 0.6091 | 0.5122 | 0.7842 |
No log | 4.0 | 92 | 0.6051 | 0.4989 | 0.6416 | 0.5613 | 0.8085 |
No log | 5.0 | 115 | 0.5500 | 0.5501 | 0.6449 | 0.5937 | 0.8243 |
No log | 6.0 | 138 | 0.5272 | 0.5351 | 0.6892 | 0.6025 | 0.8277 |
No log | 7.0 | 161 | 0.5256 | 0.5426 | 0.7143 | 0.6167 | 0.8316 |
No log | 8.0 | 184 | 0.4943 | 0.5583 | 0.7582 | 0.6431 | 0.8479 |
No log | 9.0 | 207 | 0.4196 | 0.6217 | 0.7475 | 0.6788 | 0.8773 |
No log | 10.0 | 230 | 0.4065 | 0.6270 | 0.7789 | 0.6948 | 0.8850 |
No log | 11.0 | 253 | 0.4367 | 0.6012 | 0.8062 | 0.6887 | 0.8776 |
No log | 12.0 | 276 | 0.3917 | 0.6301 | 0.8125 | 0.7098 | 0.8915 |
No log | 13.0 | 299 | 0.3563 | 0.6736 | 0.8191 | 0.7393 | 0.9042 |
No log | 14.0 | 322 | 0.3654 | 0.6653 | 0.8335 | 0.7400 | 0.9040 |
No log | 15.0 | 345 | 0.3637 | 0.6611 | 0.8439 | 0.7414 | 0.9057 |
No log | 16.0 | 368 | 0.3522 | 0.6785 | 0.8453 | 0.7528 | 0.9100 |
No log | 17.0 | 391 | 0.3469 | 0.6841 | 0.8472 | 0.7569 | 0.9115 |
No log | 18.0 | 414 | 0.3520 | 0.6821 | 0.8490 | 0.7565 | 0.9110 |
No log | 19.0 | 437 | 0.3485 | 0.6848 | 0.8494 | 0.7583 | 0.9121 |
No log | 20.0 | 460 | 0.3493 | 0.6836 | 0.8494 | 0.7575 | 0.9116 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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