---
license: mit
base_model: flaubert/flaubert_small_cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bank-transactions-statements-classification
  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-transactions-statements-classification

This model is a fine-tuned version of [flaubert/flaubert_small_cased](https://huggingface.co/flaubert/flaubert_small_cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1580
- Accuracy: 0.7403
- F1 Macro: 0.7519
- F1 Weighted: 0.7311

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| No log        | 1.0   | 172  | 3.0068          | 0.2810   | 0.0900   | 0.2272      |
| No log        | 2.0   | 344  | 2.2030          | 0.4587   | 0.2989   | 0.4108      |
| 3.2096        | 3.0   | 516  | 1.7050          | 0.5766   | 0.5069   | 0.5466      |
| 3.2096        | 4.0   | 688  | 1.4428          | 0.6538   | 0.6220   | 0.6359      |
| 3.2096        | 5.0   | 860  | 1.2683          | 0.7031   | 0.6925   | 0.6899      |
| 1.7054        | 6.0   | 1032 | 1.2496          | 0.7164   | 0.7215   | 0.7068      |
| 1.7054        | 7.0   | 1204 | 1.2271          | 0.7217   | 0.7316   | 0.7084      |
| 1.7054        | 8.0   | 1376 | 1.1727          | 0.7364   | 0.7465   | 0.7273      |
| 1.2526        | 9.0   | 1548 | 1.1705          | 0.7410   | 0.7495   | 0.7317      |
| 1.2526        | 10.0  | 1720 | 1.1580          | 0.7403   | 0.7519   | 0.7311      |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1