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roberta-large-ner-qlorafinetune-runs-colab-batch16
edbanguera/roberta-large-ner-qlorafinetune-runs-colab-batch16
roberta-large-ner-qlorafinetune-runs-colab-batch16 is a machine learning model from edbanguera. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Dec 12, 2024
- Updated
- Dec 12, 2024
- SHA
- 739ab4d0
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
roberta-large-ner-qlorafinetune-runs-colab-batch16
This model is a fine-tuned version of PlanTL-GOB-ES/roberta-large-bne-capitel-ner on the biobert_json dataset. It achieves the following results on the evaluation set:
- Loss: 0.0970
- Precision: 0.9580
- Recall: 0.9678
- F1: 0.9629
- Accuracy: 0.9821
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2335 | 1.0 | 612 | 0.0947 | 0.9466 | 0.9517 | 0.9492 | 0.9742 |
| 0.0829 | 2.0 | 1224 | 0.0838 | 0.9446 | 0.9653 | 0.9548 | 0.9779 |
| 0.0593 | 3.0 | 1836 | 0.0753 | 0.9491 | 0.9707 | 0.9598 | 0.9811 |
| 0.0463 | 4.0 | 2448 | 0.0836 | 0.9546 | 0.9687 | 0.9616 | 0.9816 |
| 0.0296 | 5.0 | 3060 | 0.0861 | 0.9572 | 0.9616 | 0.9594 | 0.9797 |
| 0.025 | 6.0 | 3672 | 0.0898 | 0.9562 | 0.9635 | 0.9598 | 0.9801 |
| 0.0191 | 7.0 | 4284 | 0.0871 | 0.9570 | 0.9677 | 0.9623 | 0.9816 |
| 0.0184 | 8.0 | 4896 | 0.0898 | 0.9543 | 0.9655 | 0.9599 | 0.9805 |
| 0.013 | 9.0 | 5508 | 0.0933 | 0.9582 | 0.9681 | 0.9631 | 0.9822 |
| 0.0107 | 10.0 | 6120 | 0.0970 | 0.9580 | 0.9678 | 0.9629 | 0.9821 |
Framework versions
- PEFT 0.13.2
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Library
- peft
- License
- apache-2.0
- Created
- Dec 12, 2024
- Updated
- Dec 12, 2024