---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-banking-intent
  results: []
datasets:
- hf-tuner/banking-intent
language:
- en
pipeline_tag: text-classification
---

<!-- 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. -->

# bert-banking-intent

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on 
[hf-tuner/banking-intent](https://huggingface.co/datasets/hf-tuner/banking-intent) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0079
- Accuracy: 0.9993

### How to Get Started with the Model

```py

from transformers import pipeline

classifier = pipeline("text-classification", model = "hf-tuner/bert-banking-intent")
classifier("Please help me get a new card, I reside in the United States.")
## [{'label': 'country_support', 'score': 0.997}]

```

### 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9901        | 1.0   | 626  | 1.5437          | 0.8104   |
| 0.8228        | 2.0   | 1252 | 0.5328          | 0.9335   |
| 0.3901        | 3.0   | 1878 | 0.2214          | 0.9678   |
| 0.1889        | 4.0   | 2504 | 0.1041          | 0.9830   |
| 0.0973        | 5.0   | 3130 | 0.0518          | 0.9920   |
| 0.0733        | 6.0   | 3756 | 0.0322          | 0.9944   |
| 0.0405        | 7.0   | 4382 | 0.0167          | 0.9976   |
| 0.0214        | 8.0   | 5008 | 0.0114          | 0.9988   |
| 0.0175        | 9.0   | 5634 | 0.0091          | 0.9993   |
| 0.0138        | 10.0  | 6260 | 0.0079          | 0.9993   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1