---
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: 0.8450
- F1: 0.6468

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.916         | 0.5   | 500  | 0.8835          | 0.6218 |
| 0.8783        | 1.0   | 1000 | 0.8467          | 0.6531 |
| 0.8769        | 1.5   | 1500 | 0.8581          | 0.6487 |
| 0.8499        | 2.01  | 2000 | 0.8651          | 0.6488 |
| 0.8734        | 2.51  | 2500 | 0.8908          | 0.6409 |
| 0.8597        | 3.01  | 3000 | 0.8923          | 0.6409 |
| 0.8987        | 3.51  | 3500 | 0.8999          | 0.6215 |
| 0.879         | 4.01  | 4000 | 0.9219          | 0.6220 |
| 0.8892        | 4.51  | 4500 | 0.8936          | 0.6220 |
| 0.8926        | 5.02  | 5000 | 0.8914          | 0.6226 |
| 0.975         | 5.52  | 5500 | 0.8984          | 0.6405 |
| 0.9387        | 6.02  | 6000 | 1.1061          | 0.2347 |
| 0.9446        | 6.52  | 6500 | 0.8879          | 0.6436 |
| 0.879         | 7.02  | 7000 | 0.9053          | 0.6216 |
| 0.8657        | 7.52  | 7500 | 0.8552          | 0.6446 |
| 0.8396        | 8.02  | 8000 | 0.8535          | 0.6475 |
| 0.8264        | 8.53  | 8500 | 0.8476          | 0.6519 |
| 0.8555        | 9.03  | 9000 | 0.8450          | 0.6468 |
| 0.851         | 9.53  | 9500 | 0.8807          | 0.6404 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3