---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Classifier_EUR_01
  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. -->

# Classifier_EUR_01

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8187
- Accuracy: 0.7537

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5467        | 1.0   | 2795  | 0.5496          | 0.7765   |
| 0.5311        | 2.0   | 5590  | 0.8505          | 0.7765   |
| 0.5339        | 3.0   | 8385  | 0.5301          | 0.7765   |
| 0.5273        | 4.0   | 11180 | 0.5696          | 0.7770   |
| 0.4915        | 5.0   | 13975 | 0.8418          | 0.7542   |
| 0.4574        | 6.0   | 16770 | 0.8187          | 0.7537   |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2