---
license: mit
base_model: PORTULAN/albertina-ptbr-base
tags:
- generated_from_trainer
model-index:
- name: e3_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. -->

# e3_lr2e-05

This model is a fine-tuned version of [PORTULAN/albertina-ptbr-base](https://huggingface.co/PORTULAN/albertina-ptbr-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9281

## 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: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.4061        | 0.1040 | 100  | 1.1920          |
| 1.2553        | 0.2080 | 200  | 1.1209          |
| 1.2102        | 0.3120 | 300  | 1.0971          |
| 1.1773        | 0.4160 | 400  | 1.0738          |
| 1.1432        | 0.5200 | 500  | 1.0481          |
| 1.1302        | 0.6240 | 600  | 1.0320          |
| 1.1153        | 0.7280 | 700  | 1.0243          |
| 1.1057        | 0.8320 | 800  | 1.0107          |
| 1.0976        | 0.9360 | 900  | 1.0002          |
| 1.0889        | 1.0400 | 1000 | 0.9907          |
| 1.0797        | 1.1440 | 1100 | 0.9836          |
| 1.0633        | 1.2480 | 1200 | 0.9788          |
| 1.0582        | 1.3521 | 1300 | 0.9761          |
| 1.0578        | 1.4561 | 1400 | 0.9635          |
| 1.0423        | 1.5601 | 1500 | 0.9601          |
| 1.0411        | 1.6641 | 1600 | 0.9578          |
| 1.0406        | 1.7681 | 1700 | 0.9527          |
| 1.0436        | 1.8721 | 1800 | 0.9520          |
| 1.0363        | 1.9761 | 1900 | 0.9443          |
| 1.0274        | 2.0801 | 2000 | 0.9419          |
| 1.03          | 2.1841 | 2100 | 0.9417          |
| 1.0232        | 2.2881 | 2200 | 0.9392          |
| 1.0237        | 2.3921 | 2300 | 0.9374          |
| 1.0199        | 2.4961 | 2400 | 0.9354          |
| 1.0095        | 2.6001 | 2500 | 0.9399          |
| 1.0145        | 2.7041 | 2600 | 0.9343          |
| 1.0179        | 2.8081 | 2700 | 0.9297          |
| 1.0148        | 2.9121 | 2800 | 0.9328          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1