---
library_name: transformers
base_model: ProsusAI/finbert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finbert-custom-sentiment
  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-custom-sentiment

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: 0.1984
- Accuracy: 0.9370
- Precision Macro: 0.9373
- Recall Macro: 0.9345
- F1 Macro: 0.9357
- Precision Weighted: 0.9372
- Recall Weighted: 0.9370
- F1 Weighted: 0.9369

## 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: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | Precision Weighted | Recall Weighted | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
| 0.2343        | 1.0   | 64   | 0.2211          | 0.9252   | 0.9235          | 0.9248       | 0.9239   | 0.9255             | 0.9252          | 0.9251      |
| 0.1129        | 2.0   | 128  | 0.2009          | 0.9350   | 0.9340          | 0.9330       | 0.9334   | 0.9349             | 0.9350          | 0.9349      |
| 0.1176        | 3.0   | 192  | 0.1984          | 0.9370   | 0.9373          | 0.9345       | 0.9357   | 0.9372             | 0.9370          | 0.9369      |


### Framework versions

- Transformers 4.54.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2