---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- banking77
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-banking77
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: banking77
      type: banking77
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.925
    - name: F1
      type: f1
      value: 0.925018570680639
---

<!-- 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. -->

# distilbert-base-uncased-finetuned-banking77

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: 0.2935
- Accuracy: 0.925
- F1: 0.9250

## 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: 9.686210354742596e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 126  | 1.1457          | 0.7896   | 0.7685 |
| No log        | 2.0   | 252  | 0.4673          | 0.8906   | 0.8889 |
| No log        | 3.0   | 378  | 0.3488          | 0.9150   | 0.9151 |
| 0.9787        | 4.0   | 504  | 0.3238          | 0.9180   | 0.9179 |
| 0.9787        | 5.0   | 630  | 0.3126          | 0.9225   | 0.9226 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.11.6