---
tags:
- generated_from_trainer
metrics:
- f1
- recall
- precision
model-index:
- name: sentiment-roberta-e6-b16-data2
  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-e6-b16-data2

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: 1.4505
- 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|
| No log        | 1.0   | 375  | 0.7961          | 0.7089 | 0.7089 | 0.7089    |
| 0.6924        | 2.0   | 750  | 0.6880          | 0.7601 | 0.7601 | 0.7601    |
| 0.3191        | 3.0   | 1125 | 1.1324          | 0.7520 | 0.7520 | 0.7520    |
| 0.1802        | 4.0   | 1500 | 1.2056          | 0.7682 | 0.7682 | 0.7682    |
| 0.1802        | 5.0   | 1875 | 1.3942          | 0.7736 | 0.7736 | 0.7736    |
| 0.088         | 6.0   | 2250 | 1.4505          | 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