---
tags:
- generated_from_trainer
metrics:
- f1
- recall
- precision
model-index:
- name: sentiment-roberta_base-e4-b16
  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. -->

# sentiment-roberta_base-e4-b16

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6110
- F1: 0.7385
- Recall: 0.7385
- Precision: 0.7385

## 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: 2e-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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|
| No log        | 1.0   | 375  | 0.8888          | 0.7493 | 0.7493 | 0.7493    |
| 0.461         | 2.0   | 750  | 1.1518          | 0.7493 | 0.7493 | 0.7493    |
| 0.1578        | 3.0   | 1125 | 1.5342          | 0.7358 | 0.7358 | 0.7358    |
| 0.0658        | 4.0   | 1500 | 1.6110          | 0.7385 | 0.7385 | 0.7385    |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3