---
base_model: ProsusAI/finbert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: finbert_flang-bert
  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_flang-bert

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: 0.5591
- Accuracy: 0.8612
- F1: 0.8609
- Precision: 0.8614
- Recall: 0.8612

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8272        | 1.0   | 91   | 0.7513          | 0.6849   | 0.6737 | 0.6816    | 0.6849 |
| 0.5021        | 2.0   | 182  | 0.4521          | 0.8346   | 0.8352 | 0.8385    | 0.8346 |
| 0.3117        | 3.0   | 273  | 0.4304          | 0.8440   | 0.8443 | 0.8451    | 0.8440 |
| 0.2461        | 4.0   | 364  | 0.5123          | 0.8346   | 0.8331 | 0.8373    | 0.8346 |
| 0.1517        | 5.0   | 455  | 0.5046          | 0.8393   | 0.8377 | 0.8410    | 0.8393 |
| 0.1005        | 6.0   | 546  | 0.5839          | 0.8502   | 0.8513 | 0.8562    | 0.8502 |
| 0.0847        | 7.0   | 637  | 0.5591          | 0.8612   | 0.8609 | 0.8614    | 0.8612 |
| 0.0984        | 8.0   | 728  | 0.7036          | 0.8268   | 0.8260 | 0.8343    | 0.8268 |
| 0.1664        | 9.0   | 819  | 0.6091          | 0.8346   | 0.8320 | 0.8384    | 0.8346 |
| 0.1215        | 10.0  | 910  | 0.6464          | 0.8393   | 0.8397 | 0.8475    | 0.8393 |
| 0.0881        | 11.0  | 1001 | 0.5982          | 0.8580   | 0.8563 | 0.8591    | 0.8580 |
| 0.0579        | 12.0  | 1092 | 0.6472          | 0.8596   | 0.8593 | 0.8592    | 0.8596 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1