---
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: twiiter_try15_fold1
  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. -->

# twiiter_try15_fold1

This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1718
- F1: 0.9816

## 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: 3e-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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2154        | 1.0   | 500  | 0.0921          | 0.9763 |
| 0.0689        | 2.0   | 1000 | 0.1517          | 0.9646 |
| 0.0329        | 3.0   | 1500 | 0.0965          | 0.9821 |
| 0.0102        | 4.0   | 2000 | 0.1161          | 0.9819 |
| 0.0097        | 5.0   | 2500 | 0.1399          | 0.9784 |
| 0.0028        | 6.0   | 3000 | 0.2075          | 0.9725 |
| 0.006         | 7.0   | 3500 | 0.1767          | 0.9768 |
| 0.0059        | 8.0   | 4000 | 0.1750          | 0.9775 |
| 0.0001        | 9.0   | 4500 | 0.2467          | 0.9724 |
| 0.0073        | 10.0  | 5000 | 0.1923          | 0.9754 |
| 0.0026        | 11.0  | 5500 | 0.1645          | 0.9790 |
| 0.002         | 12.0  | 6000 | 0.1862          | 0.9801 |
| 0.0008        | 13.0  | 6500 | 0.1643          | 0.98   |
| 0.0           | 14.0  | 7000 | 0.1708          | 0.9816 |
| 0.0           | 15.0  | 7500 | 0.1718          | 0.9816 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3