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---
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
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