---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finbert-finetuned-FG-SINGLE_SENTENCE-NEWS-WEIGHTED
  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-finetuned-FG-SINGLE_SENTENCE-NEWS-WEIGHTED

This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2741
- Accuracy: 0.7475
- F1: 0.7253

## 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: 6e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 249  | 0.9150          | 0.7346   | 0.6484 |
| No log        | 2.0   | 498  | 0.8837          | 0.6210   | 0.6317 |
| 1.033         | 3.0   | 747  | 0.8460          | 0.6485   | 0.6666 |
| 1.033         | 4.0   | 996  | 1.0089          | 0.6831   | 0.6909 |
| 0.5642        | 5.0   | 1245 | 1.2507          | 0.7352   | 0.7152 |
| 0.5642        | 6.0   | 1494 | 1.3241          | 0.7129   | 0.7042 |
| 0.2078        | 7.0   | 1743 | 1.5163          | 0.7528   | 0.7230 |
| 0.2078        | 8.0   | 1992 | 1.5818          | 0.7352   | 0.7236 |
| 0.1108        | 9.0   | 2241 | 1.7930          | 0.7012   | 0.7046 |
| 0.1108        | 10.0  | 2490 | 1.8262          | 0.7305   | 0.7211 |
| 0.07          | 11.0  | 2739 | 2.0415          | 0.7440   | 0.7192 |
| 0.07          | 12.0  | 2988 | 2.1260          | 0.7563   | 0.7230 |
| 0.0392        | 13.0  | 3237 | 2.1502          | 0.7528   | 0.7323 |
| 0.0392        | 14.0  | 3486 | 2.2117          | 0.7516   | 0.7270 |
| 0.0174        | 15.0  | 3735 | 2.2657          | 0.7405   | 0.7236 |
| 0.0174        | 16.0  | 3984 | 2.2741          | 0.7475   | 0.7253 |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6