metadata
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
model-index:
- name: e3_lr2e-05
results: []
e3_lr2e-05
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5721
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2771 | 0.0707 | 100 | 1.9875 |
| 2.0486 | 0.1414 | 200 | 1.8946 |
| 1.993 | 0.2121 | 300 | 1.8415 |
| 1.9532 | 0.2828 | 400 | 1.8133 |
| 1.9145 | 0.3535 | 500 | 1.7807 |
| 1.8872 | 0.4242 | 600 | 1.7534 |
| 1.8593 | 0.4949 | 700 | 1.7357 |
| 1.8447 | 0.5656 | 800 | 1.7173 |
| 1.8149 | 0.6363 | 900 | 1.7074 |
| 1.7966 | 0.7070 | 1000 | 1.7036 |
| 1.8034 | 0.7777 | 1100 | 1.6883 |
| 1.7854 | 0.8484 | 1200 | 1.6740 |
| 1.7779 | 0.9191 | 1300 | 1.6642 |
| 1.7706 | 0.9897 | 1400 | 1.6582 |
| 1.7723 | 1.0604 | 1500 | 1.6475 |
| 1.746 | 1.1311 | 1600 | 1.6463 |
| 1.7386 | 1.2018 | 1700 | 1.6399 |
| 1.7319 | 1.2725 | 1800 | 1.6385 |
| 1.7292 | 1.3432 | 1900 | 1.6230 |
| 1.7121 | 1.4139 | 2000 | 1.6204 |
| 1.7245 | 1.4846 | 2100 | 1.6152 |
| 1.7159 | 1.5553 | 2200 | 1.6103 |
| 1.7232 | 1.6260 | 2300 | 1.6114 |
| 1.6952 | 1.6967 | 2400 | 1.6099 |
| 1.6944 | 1.7674 | 2500 | 1.6012 |
| 1.6991 | 1.8381 | 2600 | 1.5970 |
| 1.6954 | 1.9088 | 2700 | 1.5933 |
| 1.698 | 1.9795 | 2800 | 1.5918 |
| 1.6857 | 2.0502 | 2900 | 1.5915 |
| 1.6783 | 2.1209 | 3000 | 1.5840 |
| 1.679 | 2.1916 | 3100 | 1.5817 |
| 1.6796 | 2.2623 | 3200 | 1.5835 |
| 1.6709 | 2.3330 | 3300 | 1.5769 |
| 1.6626 | 2.4037 | 3400 | 1.5819 |
| 1.6732 | 2.4744 | 3500 | 1.5824 |
| 1.6726 | 2.5458 | 3600 | 1.5720 |
| 1.6822 | 2.6165 | 3700 | 1.5758 |
| 1.6578 | 2.6872 | 3800 | 1.5739 |
| 1.6756 | 2.7579 | 3900 | 1.5743 |
| 1.6747 | 2.8286 | 4000 | 1.5695 |
| 1.659 | 2.8993 | 4100 | 1.5713 |
| 1.6587 | 2.9700 | 4200 | 1.5750 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1