---
library_name: transformers
base_model: adalbertojunior/distilbert-portuguese-cased
tags:
- generated_from_trainer
model-index:
- name: e500_lr2e-05
  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. -->

# e500_lr2e-05

This model is a fine-tuned version of [adalbertojunior/distilbert-portuguese-cased](https://huggingface.co/adalbertojunior/distilbert-portuguese-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3316

## 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: 200
- eval_batch_size: 400
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 6.8051        | 1.5385  | 100  | 5.4555          |
| 5.0899        | 3.0769  | 200  | 4.5164          |
| 4.3939        | 4.6154  | 300  | 3.9739          |
| 3.948         | 6.1538  | 400  | 3.6053          |
| 3.6364        | 7.6923  | 500  | 3.3412          |
| 3.391         | 9.2308  | 600  | 3.1273          |
| 3.2013        | 10.7692 | 700  | 2.9847          |
| 3.0531        | 12.3077 | 800  | 2.7862          |
| 2.9261        | 13.8462 | 900  | 2.7109          |
| 2.8132        | 15.3846 | 1000 | 2.5933          |
| 2.698         | 16.9231 | 1100 | 2.5080          |
| 2.614         | 18.4615 | 1200 | 2.4453          |
| 2.5423        | 20.0    | 1300 | 2.3267          |
| 2.4675        | 21.5385 | 1400 | 2.2761          |
| 2.4105        | 23.0769 | 1500 | 2.2385          |
| 2.3405        | 24.6154 | 1600 | 2.1717          |
| 2.2862        | 26.1538 | 1700 | 2.1134          |
| 2.2324        | 27.6923 | 1800 | 2.0816          |
| 2.1954        | 29.2308 | 1900 | 2.0319          |
| 2.145         | 30.7692 | 2000 | 1.9917          |
| 2.1001        | 32.3077 | 2100 | 1.9738          |
| 2.0688        | 33.8462 | 2200 | 1.9215          |
| 2.024         | 35.3846 | 2300 | 1.8910          |
| 1.99          | 36.9231 | 2400 | 1.8697          |
| 1.9524        | 38.4615 | 2500 | 1.8273          |
| 1.9288        | 40.0    | 2600 | 1.7972          |
| 1.8957        | 41.5385 | 2700 | 1.7696          |
| 1.8713        | 43.0769 | 2800 | 1.7486          |
| 1.8427        | 44.6154 | 2900 | 1.7461          |
| 1.8155        | 46.1538 | 3000 | 1.6993          |
| 1.7914        | 47.6923 | 3100 | 1.6781          |
| 1.766         | 49.2308 | 3200 | 1.6483          |
| 1.738         | 50.7692 | 3300 | 1.6227          |
| 1.7167        | 52.3077 | 3400 | 1.5883          |
| 1.6781        | 53.8462 | 3500 | 1.5695          |
| 1.658         | 55.3846 | 3600 | 1.5469          |
| 1.6276        | 56.9231 | 3700 | 1.5451          |
| 1.6131        | 58.4615 | 3800 | 1.5046          |
| 1.5916        | 60.0    | 3900 | 1.4997          |
| 1.5746        | 61.5385 | 4000 | 1.4709          |
| 1.5638        | 63.0769 | 4100 | 1.4615          |
| 1.5395        | 64.6154 | 4200 | 1.4542          |
| 1.5291        | 66.1538 | 4300 | 1.4323          |
| 1.5115        | 67.6923 | 4400 | 1.4036          |
| 1.4885        | 69.2308 | 4500 | 1.3822          |
| 1.4706        | 70.7692 | 4600 | 1.3732          |
| 1.4611        | 72.3077 | 4700 | 1.3625          |
| 1.4393        | 73.8462 | 4800 | 1.3662          |
| 1.4321        | 75.3846 | 4900 | 1.3556          |
| 1.4108        | 76.9231 | 5000 | 1.3566          |
| 1.4054        | 78.4615 | 5100 | 1.2953          |
| 1.3863        | 80.0    | 5200 | 1.3333          |
| 1.3674        | 81.5385 | 5300 | 1.3210          |
| 1.3578        | 83.0769 | 5400 | 1.3029          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1