File size: 2,464 Bytes
3117cc6 9b13431 3117cc6 9b13431 3117cc6 9b13431 3117cc6 9b13431 3117cc6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
license: apache-2.0
base_model: PlanTL-GOB-ES/roberta-base-biomedical-es
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biomedical-roberta-finetuned-iomed_task
results: []
---
<!-- 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. -->
# biomedical-roberta-finetuned-iomed_task
This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-es) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0160
- Precision: 0.1934
- Recall: 0.3953
- F1: 0.2597
- Accuracy: 0.7681
## 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: 2.2e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 13
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 2.1178 | 1.3 | 988 | 1.3039 | 0.0802 | 0.2102 | 0.1161 | 0.7321 |
| 1.2448 | 2.6 | 1976 | 1.1444 | 0.1161 | 0.2811 | 0.1643 | 0.7568 |
| 1.0297 | 3.9 | 2964 | 1.0724 | 0.1484 | 0.3299 | 0.2047 | 0.7658 |
| 0.9496 | 5.2 | 3952 | 1.0342 | 0.1676 | 0.3583 | 0.2284 | 0.7685 |
| 0.88 | 6.5 | 4940 | 1.0465 | 0.1805 | 0.3795 | 0.2446 | 0.7660 |
| 0.8168 | 7.8 | 5928 | 1.0253 | 0.1713 | 0.3638 | 0.2329 | 0.7624 |
| 0.7863 | 9.1 | 6916 | 1.0293 | 0.1754 | 0.3622 | 0.2364 | 0.7641 |
| 0.784 | 10.4 | 7904 | 1.0159 | 0.1920 | 0.3890 | 0.2571 | 0.7648 |
| 0.7161 | 11.7 | 8892 | 1.0121 | 0.1853 | 0.3819 | 0.2495 | 0.7654 |
| 0.7629 | 13.0 | 9880 | 1.0160 | 0.1934 | 0.3953 | 0.2597 | 0.7681 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|