---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: roberta-base-Roberta-Model
  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-base-Roberta-Model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7350
- F1: 0.6663

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.8512        | 0.5   | 500  | 0.7909          | 0.6405 |
| 0.7992        | 1.0   | 1000 | 0.8753          | 0.6407 |
| 0.7667        | 1.5   | 1500 | 0.7786          | 0.6428 |
| 0.7583        | 2.01  | 2000 | 0.7407          | 0.6593 |
| 0.7415        | 2.51  | 2500 | 0.7564          | 0.6555 |
| 0.7337        | 3.01  | 3000 | 0.7536          | 0.6526 |
| 0.7224        | 3.51  | 3500 | 0.7777          | 0.6126 |
| 0.7067        | 4.01  | 4000 | 0.7790          | 0.6552 |
| 0.6693        | 4.51  | 4500 | 0.7497          | 0.6665 |
| 0.6744        | 5.02  | 5000 | 0.7350          | 0.6663 |
| 0.6546        | 5.52  | 5500 | 0.7865          | 0.6714 |
| 0.6725        | 6.02  | 6000 | 0.7639          | 0.6721 |
| 0.6361        | 6.52  | 6500 | 0.7780          | 0.6917 |
| 0.6268        | 7.02  | 7000 | 0.7905          | 0.6893 |
| 0.619         | 7.52  | 7500 | 0.7644          | 0.6991 |
| 0.6008        | 8.02  | 8000 | 0.7473          | 0.7086 |
| 0.5824        | 8.53  | 8500 | 0.7601          | 0.7009 |
| 0.5687        | 9.03  | 9000 | 0.7795          | 0.6888 |
| 0.5466        | 9.53  | 9500 | 0.7925          | 0.7045 |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3