|
--- |
|
license: apache-2.0 |
|
base_model: distilbert-base-multilingual-cased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: modelo_racismo_13_dez |
|
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. --> |
|
|
|
# modelo_racismo_13_dez |
|
|
|
This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0996 |
|
- F1: 0.9861 |
|
- Accuracy: 0.9844 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 8 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:| |
|
| 0.6264 | 1.0 | 643 | 0.6426 | 0.8423 | 0.8179 | |
|
| 0.7407 | 2.0 | 1286 | 0.4516 | 0.9121 | 0.9019 | |
|
| 0.5953 | 3.0 | 1929 | 0.2944 | 0.9492 | 0.9416 | |
|
| 0.3275 | 4.0 | 2572 | 0.3128 | 0.9522 | 0.9447 | |
|
| 0.3185 | 5.0 | 3215 | 0.1861 | 0.9732 | 0.9696 | |
|
| 0.1702 | 6.0 | 3858 | 0.1225 | 0.9818 | 0.9798 | |
|
| 0.1411 | 7.0 | 4501 | 0.1027 | 0.9854 | 0.9837 | |
|
| 0.0895 | 8.0 | 5144 | 0.0996 | 0.9861 | 0.9844 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|