roberta-base-bne-ner
This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3159
- Precision: 0.8517
- Recall: 0.8933
- F1: 0.8720
- Accuracy: 0.9384
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 280 | 0.3006 | 0.7961 | 0.8563 | 0.8251 | 0.9164 |
| 0.4008 | 2.0 | 560 | 0.2984 | 0.7918 | 0.8622 | 0.8255 | 0.9203 |
| 0.4008 | 3.0 | 840 | 0.2324 | 0.8401 | 0.8563 | 0.8481 | 0.9343 |
| 0.1014 | 4.0 | 1120 | 0.2394 | 0.8242 | 0.8889 | 0.8553 | 0.9414 |
| 0.1014 | 5.0 | 1400 | 0.2674 | 0.8469 | 0.8933 | 0.8695 | 0.9371 |
| 0.0435 | 6.0 | 1680 | 0.2815 | 0.8255 | 0.8830 | 0.8533 | 0.9375 |
| 0.0435 | 7.0 | 1960 | 0.2713 | 0.8516 | 0.8844 | 0.8677 | 0.9444 |
| 0.0233 | 8.0 | 2240 | 0.2745 | 0.8541 | 0.8933 | 0.8733 | 0.9437 |
| 0.0177 | 9.0 | 2520 | 0.3383 | 0.8336 | 0.8978 | 0.8645 | 0.9350 |
| 0.0177 | 10.0 | 2800 | 0.2858 | 0.8606 | 0.8963 | 0.8781 | 0.9419 |
| 0.013 | 11.0 | 3080 | 0.2956 | 0.8350 | 0.8919 | 0.8625 | 0.9403 |
| 0.013 | 12.0 | 3360 | 0.3097 | 0.8423 | 0.9022 | 0.8712 | 0.9380 |
| 0.0104 | 13.0 | 3640 | 0.3158 | 0.8443 | 0.8919 | 0.8674 | 0.9380 |
| 0.0104 | 14.0 | 3920 | 0.3171 | 0.8493 | 0.8933 | 0.8708 | 0.9387 |
| 0.0088 | 15.0 | 4200 | 0.3159 | 0.8517 | 0.8933 | 0.8720 | 0.9384 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for manucos/roberta-base-bne-ner
Base model
PlanTL-GOB-ES/roberta-base-bne