---
library_name: transformers
base_model: ProsusAI/finbert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finance-sentiment-classifier
  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. -->

# finance-sentiment-classifier

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: 0.3186
- Accuracy: 0.9203
- F1: 0.9202

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.6005        | 0.1999 | 500  | 0.5220          | 0.7970   | 0.7954 |
| 0.4518        | 0.3998 | 1000 | 0.3991          | 0.8546   | 0.8540 |
| 0.3773        | 0.5998 | 1500 | 0.3231          | 0.8813   | 0.8808 |
| 0.3375        | 0.7997 | 2000 | 0.3025          | 0.8878   | 0.8881 |
| 0.2982        | 0.9996 | 2500 | 0.2735          | 0.8977   | 0.8971 |
| 0.2057        | 1.1995 | 3000 | 0.3028          | 0.9035   | 0.9026 |
| 0.2001        | 1.3994 | 3500 | 0.2624          | 0.9123   | 0.9119 |
| 0.2034        | 1.5994 | 4000 | 0.2450          | 0.9171   | 0.9170 |
| 0.1631        | 1.7993 | 4500 | 0.2547          | 0.9180   | 0.9179 |
| 0.1691        | 1.9992 | 5000 | 0.2379          | 0.9189   | 0.9189 |
| 0.1077        | 2.1991 | 5500 | 0.2982          | 0.9190   | 0.9186 |
| 0.1288        | 2.3990 | 6000 | 0.2772          | 0.9201   | 0.9199 |
| 0.1114        | 2.5990 | 6500 | 0.2847          | 0.9220   | 0.9220 |
| 0.1128        | 2.7989 | 7000 | 0.2879          | 0.9234   | 0.9233 |
| 0.0969        | 2.9988 | 7500 | 0.2920          | 0.9236   | 0.9234 |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.1+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2