File size: 2,188 Bytes
44e375e |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep8_lr3
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. -->
# BERT_ep8_lr3
This model is a fine-tuned version of [ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT](https://huggingface.co/ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1048
- Precision: 0.7641
- Recall: 0.8235
- F1: 0.7927
- Accuracy: 0.9666
## 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-07
- 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: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 467 | 0.1361 | 0.6936 | 0.7475 | 0.7195 | 0.9568 |
| 0.1814 | 2.0 | 934 | 0.1187 | 0.7168 | 0.7849 | 0.7493 | 0.9613 |
| 0.1202 | 3.0 | 1401 | 0.1118 | 0.7361 | 0.7990 | 0.7662 | 0.9635 |
| 0.1109 | 4.0 | 1868 | 0.1088 | 0.7508 | 0.8072 | 0.7780 | 0.9650 |
| 0.1006 | 5.0 | 2335 | 0.1069 | 0.7570 | 0.8158 | 0.7853 | 0.9657 |
| 0.0987 | 6.0 | 2802 | 0.1056 | 0.7604 | 0.8191 | 0.7887 | 0.9662 |
| 0.0969 | 7.0 | 3269 | 0.1050 | 0.7651 | 0.8224 | 0.7927 | 0.9665 |
| 0.0993 | 8.0 | 3736 | 0.1048 | 0.7641 | 0.8235 | 0.7927 | 0.9666 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
|