---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- banking77
metrics:
- accuracy
model-index:
- name: banking-intent-distilbert-classifier
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: banking77
      type: banking77
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.925
---

<!-- 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. -->

# banking-intent-distilbert-classifier

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the banking77 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3307
- Accuracy: 0.925

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0124        | 1.0   | 313  | 0.3307          | 0.925    |
| 0.0102        | 2.0   | 626  | 0.3331          | 0.9289   |
| 0.0077        | 3.0   | 939  | 0.3381          | 0.9282   |
| 0.0062        | 4.0   | 1252 | 0.3406          | 0.9276   |
| 0.0059        | 5.0   | 1565 | 0.3423          | 0.9282   |
| 0.0045        | 6.0   | 1878 | 0.3445          | 0.9282   |
| 0.0046        | 7.0   | 2191 | 0.3458          | 0.9286   |
| 0.0041        | 8.0   | 2504 | 0.3470          | 0.9286   |
| 0.0038        | 9.0   | 2817 | 0.3472          | 0.9286   |
| 0.0034        | 10.0  | 3130 | 0.3475          | 0.9286   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0