---
library_name: transformers
base_model: models/distill-robertalex-3L-trained
tags:
- generated_from_trainer
datasets:
- adalbertojunior/entities
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: test_v6
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: adalbertojunior/entities
      type: adalbertojunior/entities
      config: segmentacao
      split: validation
      args: segmentacao
    metrics:
    - name: Precision
      type: precision
      value: 0.7678083439606486
    - name: Recall
      type: recall
      value: 0.8550415905863258
    - name: F1
      type: f1
      value: 0.8090804377039739
    - name: Accuracy
      type: accuracy
      value: 0.9699217442249749
---

<!-- 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. -->

# test_v6

This model is a fine-tuned version of [models/distill-robertalex-3L-trained](https://huggingface.co/models/distill-robertalex-3L-trained) on the adalbertojunior/entities dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1536
- Precision: 0.7678
- Recall: 0.8550
- F1: 0.8091
- Accuracy: 0.9699

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20.0

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0925        | 19.3898 | 7000 | 0.1536          | 0.7678    | 0.8550 | 0.8091 | 0.9699   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.0.1
- Tokenizers 0.21.0