---
library_name: transformers
base_model: ProsusAI/finbert
tags:
- finBERT
- sequence-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finBERT-phraseBank
  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-phraseBank

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: 0.4035
- Accuracy: 0.8557
- F1 Macro: 0.8299
- Precision Macro: 0.8246
- Recall Macro: 0.8359
- F1 Weighted: 0.8556
- Precision Weighted: 0.8559
- Recall Weighted: 0.8557

## 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: 42
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | F1 Weighted | Precision Weighted | Recall Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:-----------:|:------------------:|:---------------:|
| 0.5357        | 1.0   | 243  | 0.4582          | 0.8258   | 0.7967   | 0.8014          | 0.7968       | 0.8235      | 0.8256             | 0.8258          |
| 0.4427        | 2.0   | 486  | 0.4090          | 0.8371   | 0.8098   | 0.8037          | 0.8186       | 0.8366      | 0.8375             | 0.8371          |
| 0.2711        | 3.0   | 729  | 0.4035          | 0.8557   | 0.8299   | 0.8246          | 0.8359       | 0.8556      | 0.8559             | 0.8557          |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1