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RoBERTa-large-PM-M3-Voc-hf-finetuned-ner-v2
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5003
- Precision: 0.3319
- Recall: 0.2149
- F1: 0.2609
- Accuracy: 0.8211
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 54 | 0.5106 | 0.2273 | 0.1003 | 0.1392 | 0.8194 |
| No log | 2.0 | 108 | 0.4781 | 0.3122 | 0.2120 | 0.2526 | 0.8226 |
| No log | 3.0 | 162 | 0.5003 | 0.3319 | 0.2149 | 0.2609 | 0.8211 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
