File size: 2,041 Bytes
d67e077 ec8bc0e d67e077 ec8bc0e d67e077 ec8bc0e d67e077 ec8bc0e d67e077 ec8bc0e d67e077 ec8bc0e d67e077 ec8bc0e d67e077 ec8bc0e d67e077 ec8bc0e d67e077 ec8bc0e | 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 | ---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: bert-base-multilingual-cased-ptbr
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-base-multilingual-cased-ptbr
This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1647
- Accuracy: 0.7960
- F1 Binary: 0.4699
- Precision: 0.3799
- Recall: 0.6158
## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 33
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Binary | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:---------:|:------:|
| No log | 1.0 | 167 | 0.1285 | 0.6951 | 0.4180 | 0.2904 | 0.7455 |
| No log | 2.0 | 334 | 0.1304 | 0.7048 | 0.4122 | 0.2913 | 0.7048 |
| 0.1094 | 3.0 | 501 | 0.1223 | 0.7336 | 0.4477 | 0.3218 | 0.7354 |
| 0.1094 | 4.0 | 668 | 0.1647 | 0.7960 | 0.4699 | 0.3799 | 0.6158 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|