---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
model-index:
- name: categories-estimation
  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. -->

# categories-estimation

This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training Metrics

Step	Training Loss	Validation Loss	F1	Accuracy
100	0.257000	0.432904	0.853367	0.905234
200	0.241600	0.431226	0.848656	0.903030
300	0.242200	0.407710	0.865890	0.908356
400	0.201600	0.375613	0.881634	0.918825
500	0.181400	0.378719	0.879368	0.916988
600	0.168800	0.361804	0.885401	0.920478

## Evaluation Metrics

{'eval_loss': 0.3545467257499695,
 'eval_F1': 0.8847876543649995,
 'eval_Accuracy': 0.9213957759412305,
 'eval_runtime': 14.8305,
 'eval_samples_per_second': 367.149,
 'eval_steps_per_second': 45.919,
 'epoch': 1.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0