---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
model-index:
- name: ft-bert-base-uncased-for-sentiment-classification
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ft-bert-base-uncased-for-sentiment-classification

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the https://huggingface.co./datasets/takala/financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1120

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1649        | 1.0   | 128  | 0.1319          |
| 0.1322        | 2.0   | 256  | 0.1232          |
| 0.0092        | 3.0   | 384  | 0.1120          |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1