clinical_bert
This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on PlanTL-GOB-ES/pharmaconer. It achieves the following results on the evaluation and test set:
- Validation Loss: 1.6020
- Test Loss: 1.6591
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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 100
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.78 | 100 | 1.9485 |
| No log | 1.56 | 200 | 1.8681 |
| No log | 2.34 | 300 | 1.8152 |
| No log | 3.12 | 400 | 1.7886 |
| 1.9285 | 3.91 | 500 | 1.7309 |
| 1.9285 | 4.69 | 600 | 1.6810 |
| 1.9285 | 5.47 | 700 | 1.7065 |
| 1.9285 | 6.25 | 800 | 1.7067 |
| 1.9285 | 7.03 | 900 | 1.7312 |
| 1.6644 | 7.81 | 1000 | 1.7006 |
| 1.6644 | 8.59 | 1100 | 1.6736 |
| 1.6644 | 9.38 | 1200 | 1.6846 |
| 1.6644 | 10.16 | 1300 | 1.6621 |
| 1.6644 | 10.94 | 1400 | 1.6381 |
| 1.5247 | 11.72 | 1500 | 1.6281 |
| 1.5247 | 12.5 | 1600 | 1.6605 |
| 1.5247 | 13.28 | 1700 | 1.6770 |
| 1.5247 | 14.06 | 1800 | 1.6666 |
| 1.5247 | 14.84 | 1900 | 1.6620 |
| 1.4334 | 15.62 | 2000 | 1.6677 |
| 1.4334 | 16.41 | 2100 | 1.6311 |
| 1.4334 | 17.19 | 2200 | 1.6743 |
| 1.4334 | 17.97 | 2300 | 1.6586 |
| 1.4334 | 18.75 | 2400 | 1.6086 |
| 1.3423 | 19.53 | 2500 | 1.6229 |
| 1.3423 | 20.31 | 2600 | 1.6475 |
| 1.3423 | 21.09 | 2700 | 1.6388 |
| 1.3423 | 21.88 | 2800 | 1.6275 |
| 1.3423 | 22.66 | 2900 | 1.6372 |
| 1.2712 | 23.44 | 3000 | 1.6345 |
| 1.2712 | 24.22 | 3100 | 1.6442 |
| 1.2712 | 25.0 | 3200 | 1.6864 |
| 1.2712 | 25.78 | 3300 | 1.6139 |
| 1.2712 | 26.56 | 3400 | 1.6161 |
| 1.215 | 27.34 | 3500 | 1.6491 |
| 1.215 | 28.12 | 3600 | 1.6442 |
| 1.215 | 28.91 | 3700 | 1.6409 |
| 1.215 | 29.69 | 3800 | 1.6539 |
| 1.215 | 30.47 | 3900 | 1.6052 |
| 1.1652 | 31.25 | 4000 | 1.6459 |
| 1.1652 | 32.03 | 4100 | 1.6362 |
| 1.1652 | 32.81 | 4200 | 1.6413 |
| 1.1652 | 33.59 | 4300 | 1.6377 |
| 1.1652 | 34.38 | 4400 | 1.6344 |
| 1.1213 | 35.16 | 4500 | 1.6406 |
| 1.1213 | 35.94 | 4600 | 1.6113 |
| 1.1213 | 36.72 | 4700 | 1.6410 |
| 1.1213 | 37.5 | 4800 | 1.6378 |
| 1.1213 | 38.28 | 4900 | 1.6341 |
| 1.0939 | 39.06 | 5000 | 1.6020 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3