Negation_Scope_Detection_SFU_Spanish_NLP-CIC-WFU_DisTEMIST_fine_tuned
This model is a fine-tuned version of ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3219
- Precision: 0.7403
- Recall: 0.7571
- F1: 0.7486
- Accuracy: 0.9518
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: 5e-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: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 72 | 0.2142 | 0.5227 | 0.6497 | 0.5793 | 0.9267 |
| No log | 2.0 | 144 | 0.2019 | 0.625 | 0.7062 | 0.6631 | 0.9420 |
| No log | 3.0 | 216 | 0.3089 | 0.6444 | 0.6554 | 0.6499 | 0.9432 |
| No log | 4.0 | 288 | 0.2376 | 0.6952 | 0.7345 | 0.7143 | 0.9478 |
| No log | 5.0 | 360 | 0.2876 | 0.7037 | 0.7514 | 0.7268 | 0.9538 |
| No log | 6.0 | 432 | 0.3077 | 0.7278 | 0.7401 | 0.7339 | 0.9534 |
| 0.091 | 7.0 | 504 | 0.3219 | 0.7403 | 0.7571 | 0.7486 | 0.9518 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1