---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: Finetuned-Roberta-Base-Sentiment-identifier
  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. -->

# Finetuned-Roberta-Base-Sentiment-identifier

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: 0.7332
- F1: 0.6622

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.8545        | 0.5   | 500  | 0.8251          | 0.6428 |
| 0.7952        | 1.0   | 1000 | 0.7831          | 0.6445 |
| 0.7962        | 1.5   | 1500 | 0.7935          | 0.6495 |
| 0.7669        | 2.01  | 2000 | 0.7544          | 0.6520 |
| 0.7468        | 2.51  | 2500 | 0.7614          | 0.6724 |
| 0.76          | 3.01  | 3000 | 0.7332          | 0.6622 |
| 0.7352        | 3.51  | 3500 | 0.8651          | 0.6036 |
| 0.7454        | 4.01  | 4000 | 0.7420          | 0.6584 |
| 0.7302        | 4.51  | 4500 | 0.7652          | 0.6573 |
| 0.7099        | 5.02  | 5000 | 0.7372          | 0.6697 |
| 0.73          | 5.52  | 5500 | 0.7806          | 0.6654 |
| 0.7265        | 6.02  | 6000 | 0.7476          | 0.6656 |
| 0.7092        | 6.52  | 6500 | 0.7632          | 0.6535 |
| 0.7322        | 7.02  | 7000 | 0.8017          | 0.6126 |
| 0.7168        | 7.52  | 7500 | 0.8046          | 0.6711 |
| 0.7279        | 8.02  | 8000 | 0.7734          | 0.6652 |
| 0.6884        | 8.53  | 8500 | 0.7806          | 0.6662 |
| 0.6942        | 9.03  | 9000 | 0.7790          | 0.6670 |
| 0.6865        | 9.53  | 9500 | 0.7835          | 0.6650 |


### Framework versions

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