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

# distilbert_EPU

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0592
- Accuracy: 0.7291

## 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: 1e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4904        | 1.0   | 699  | 0.5631          | 0.7077   |
| 0.5241        | 2.0   | 1398 | 0.5150          | 0.7458   |
| 0.3692        | 3.0   | 2097 | 0.5419          | 0.7501   |
| 0.3366        | 4.0   | 2796 | 0.6243          | 0.7430   |
| 0.2657        | 5.0   | 3495 | 0.7257          | 0.7358   |
| 0.2303        | 6.0   | 4194 | 0.8840          | 0.7349   |
| 0.0503        | 7.0   | 4893 | 1.0307          | 0.7291   |
| 0.0732        | 8.0   | 5592 | 1.0592          | 0.7291   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1