---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta_large-chunking_0728_v2
  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. -->

# roberta_large-chunking_0728_v2

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5270
- Precision: 0.6228
- Recall: 0.6467
- F1: 0.6345
- Accuracy: 0.8153

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 125  | 0.5667          | 0.4931    | 0.5415 | 0.5162 | 0.7397   |
| No log        | 2.0   | 250  | 0.4839          | 0.5484    | 0.5894 | 0.5682 | 0.7874   |
| No log        | 3.0   | 375  | 0.4822          | 0.5997    | 0.6341 | 0.6164 | 0.8085   |
| 0.4673        | 4.0   | 500  | 0.5117          | 0.6023    | 0.6373 | 0.6193 | 0.8120   |
| 0.4673        | 5.0   | 625  | 0.5270          | 0.6228    | 0.6467 | 0.6345 | 0.8153   |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1