---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilroberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bank-transaction-classification-distilroberta-base-v1
  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. -->

# bank-transaction-classification-distilroberta-base-v1

This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5173
- Accuracy: 0.8850

## 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: 45
- eval_batch_size: 45
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step   | Accuracy | Validation Loss |
|:-------------:|:-----:|:------:|:--------:|:---------------:|
| 0.6326        | 1.0   | 4596   | 0.8358   | 0.5800          |
| 0.4676        | 2.0   | 9192   | 0.8571   | 0.4992          |
| 0.3977        | 3.0   | 13788  | 0.8599   | 0.4680          |
| 0.3654        | 4.0   | 18384  | 0.8653   | 0.4636          |
| 0.3437        | 5.0   | 22980  | 0.8683   | 0.4650          |
| 0.3183        | 6.0   | 27576  | 0.8724   | 0.4453          |
| 0.296         | 7.0   | 32172  | 0.8706   | 0.4521          |
| 0.2379        | 8.0   | 36768  | 0.8760   | 0.4299          |
| 0.2772        | 9.0   | 41364  | 0.8837   | 0.4520          |
| 0.2488        | 10.0  | 45960  | 0.8776   | 0.4627          |
| 0.2589        | 11.0  | 50556  | 0.8786   | 0.4711          |
| 0.2317        | 12.0  | 55152  | 0.8801   | 0.4677          |
| 0.2179        | 13.0  | 59748  | 0.8828   | 0.4698          |
| 0.2216        | 14.0  | 64344  | 0.8798   | 0.4736          |
| 0.1983        | 15.0  | 68940  | 0.8802   | 0.4788          |
| 0.2068        | 16.0  | 73536  | 0.8817   | 0.4959          |
| 0.2034        | 17.0  | 78132  | 0.8824   | 0.4849          |
| 0.2116        | 18.0  | 82728  | 0.8837   | 0.4957          |
| 0.2152        | 19.0  | 87324  | 0.8833   | 0.4883          |
| 0.2021        | 20.0  | 91920  | 0.8855   | 0.5119          |
| 0.1962        | 21.0  | 96516  | 0.5030   | 0.8855          |
| 0.1836        | 22.0  | 101112 | 0.5089   | 0.8855          |
| 0.1944        | 23.0  | 105708 | 0.5114   | 0.8851          |
| 0.1785        | 24.0  | 110304 | 0.5157   | 0.8852          |
| 0.1802        | 25.0  | 114900 | 0.5173   | 0.8850          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1