---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: finbert-tone-finetuned-fintwitter-classification
  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. -->

# finbert-tone-finetuned-fintwitter-classification

This model is a fine-tuned version of [yiyanghkust/finbert-tone](https://huggingface.co/yiyanghkust/finbert-tone) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4236
- Accuracy: 0.8823
- F1: 0.8823
- Precision: 0.8825
- Recall: 0.8823

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6385        | 1.0   | 597   | 0.3688          | 0.8668   | 0.8693 | 0.8744    | 0.8668 |
| 0.3044        | 2.0   | 1194  | 0.3994          | 0.8744   | 0.8726 | 0.8739    | 0.8744 |
| 0.1833        | 3.0   | 1791  | 0.6212          | 0.8781   | 0.8764 | 0.8762    | 0.8781 |
| 0.1189        | 4.0   | 2388  | 0.8370          | 0.8740   | 0.8743 | 0.8748    | 0.8740 |
| 0.0759        | 5.0   | 2985  | 0.9107          | 0.8807   | 0.8798 | 0.8796    | 0.8807 |
| 0.0291        | 6.0   | 3582  | 0.9711          | 0.8836   | 0.8825 | 0.8821    | 0.8836 |
| 0.0314        | 7.0   | 4179  | 1.1305          | 0.8819   | 0.8811 | 0.8812    | 0.8819 |
| 0.0217        | 8.0   | 4776  | 1.0190          | 0.8811   | 0.8813 | 0.8816    | 0.8811 |
| 0.0227        | 9.0   | 5373  | 1.1940          | 0.8844   | 0.8832 | 0.8838    | 0.8844 |
| 0.0156        | 10.0  | 5970  | 1.2595          | 0.8752   | 0.8768 | 0.8801    | 0.8752 |
| 0.0135        | 11.0  | 6567  | 1.1931          | 0.8760   | 0.8768 | 0.8780    | 0.8760 |
| 0.009         | 12.0  | 7164  | 1.2154          | 0.8857   | 0.8852 | 0.8848    | 0.8857 |
| 0.0058        | 13.0  | 7761  | 1.3874          | 0.8748   | 0.8759 | 0.8776    | 0.8748 |
| 0.009         | 14.0  | 8358  | 1.4193          | 0.8740   | 0.8754 | 0.8780    | 0.8740 |
| 0.0042        | 15.0  | 8955  | 1.2999          | 0.8807   | 0.8800 | 0.8796    | 0.8807 |
| 0.0028        | 16.0  | 9552  | 1.3428          | 0.8802   | 0.8805 | 0.8817    | 0.8802 |
| 0.0029        | 17.0  | 10149 | 1.3959          | 0.8807   | 0.8807 | 0.8810    | 0.8807 |
| 0.0022        | 18.0  | 10746 | 1.4149          | 0.8827   | 0.8823 | 0.8824    | 0.8827 |
| 0.0037        | 19.0  | 11343 | 1.4078          | 0.8840   | 0.8838 | 0.8838    | 0.8840 |
| 0.001         | 20.0  | 11940 | 1.4236          | 0.8823   | 0.8823 | 0.8825    | 0.8823 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2