File size: 2,372 Bytes
f222035 |
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 |
---
license: cc-by-4.0
tags:
- generated_from_trainer
model-index:
- name: CTEBMSP_ner_test2
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. -->
# CTEBMSP_ner_test2
This model is a fine-tuned version of [chizhikchi/Spanish_disease_finder](https://huggingface.co/chizhikchi/Spanish_disease_finder) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0586
- Diso Precision: 0.8836
- Diso Recall: 0.8902
- Diso F1: 0.8869
- Diso Number: 4052
- Overall Precision: 0.8836
- Overall Recall: 0.8902
- Overall F1: 0.8869
- Overall Accuracy: 0.9885
## 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: 4e-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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.0463 | 1.0 | 2566 | 0.0512 | 0.8791 | 0.8384 | 0.8583 | 4052 | 0.8791 | 0.8384 | 0.8583 | 0.9859 |
| 0.0204 | 2.0 | 5132 | 0.0615 | 0.8942 | 0.8655 | 0.8796 | 4052 | 0.8942 | 0.8655 | 0.8796 | 0.9875 |
| 0.0095 | 3.0 | 7698 | 0.0545 | 0.8877 | 0.8776 | 0.8826 | 4052 | 0.8877 | 0.8776 | 0.8826 | 0.9881 |
| 0.0045 | 4.0 | 10264 | 0.0586 | 0.8836 | 0.8902 | 0.8869 | 4052 | 0.8836 | 0.8902 | 0.8869 | 0.9885 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
|