---
library_name: transformers
base_model: ProsusAI/finbert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: category-finbert
  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. -->

# category-finbert

This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2288
- Accuracy: 0.5391
- Macro F1: 0.1796
- Weighted F1: 0.4589

## 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: 13
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 4.2041        | 1.0   | 836  | 2.9954          | 0.4063   | 0.0880   | 0.2977      |
| 2.6344        | 2.0   | 1672 | 2.4037          | 0.5040   | 0.1556   | 0.4178      |
| 2.1611        | 3.0   | 2508 | 2.2288          | 0.5391   | 0.1796   | 0.4589      |


### Framework versions

- Transformers 5.0.0.dev0
- Pytorch 2.9.0+cu126
- Datasets 4.3.0
- Tokenizers 0.22.1