---
tags:
- generated_from_trainer
metrics:
- f1
- recall
- precision
model-index:
- name: sentiment-roberta-e2-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-e2-b16

This model is a fine-tuned version of [siebert/sentiment-roberta-large-english](https://huggingface.co/siebert/sentiment-roberta-large-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7419
- F1: 0.7682
- Recall: 0.7682
- Precision: 0.7682

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|
| No log        | 1.0   | 375  | 0.7050          | 0.7385 | 0.7385 | 0.7385    |
| 0.7156        | 2.0   | 750  | 0.7419          | 0.7682 | 0.7682 | 0.7682    |


### Framework versions

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