---
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: 0.7452
- F1: 0.6666

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.8612        | 0.5   | 500  | 0.7837          | 0.6394 |
| 0.7964        | 1.0   | 1000 | 0.7592          | 0.6672 |
| 0.887         | 1.5   | 1500 | 0.7818          | 0.6677 |
| 0.8249        | 2.01  | 2000 | 0.8492          | 0.6540 |
| 0.7916        | 2.51  | 2500 | 0.7721          | 0.6736 |
| 0.7988        | 3.01  | 3000 | 0.8391          | 0.6230 |
| 0.8691        | 3.51  | 3500 | 0.8104          | 0.6665 |
| 0.8473        | 4.01  | 4000 | 0.7834          | 0.6687 |
| 0.7798        | 4.51  | 4500 | 0.7582          | 0.6697 |
| 0.7886        | 5.02  | 5000 | 0.8004          | 0.6499 |
| 0.9395        | 5.52  | 5500 | 0.9524          | 0.3221 |
| 0.9588        | 6.02  | 6000 | 0.9577          | 0.3224 |
| 0.9539        | 6.52  | 6500 | 0.9560          | 0.2347 |
| 0.9599        | 7.02  | 7000 | 0.9553          | 0.3222 |
| 0.9263        | 7.52  | 7500 | 0.7582          | 0.6653 |
| 0.7897        | 8.02  | 8000 | 0.7783          | 0.6682 |
| 0.7999        | 8.53  | 8500 | 0.8641          | 0.6373 |
| 0.7779        | 9.03  | 9000 | 0.7452          | 0.6666 |
| 0.761         | 9.53  | 9500 | 0.7469          | 0.6684 |


### Framework versions

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