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

# my_awesome_model

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: 0.3714
- Accuracy: 0.933

## 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: 16
- eval_batch_size: 16
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3279        | 0.32  | 500  | 0.2746          | 0.899    |
| 0.2474        | 0.64  | 1000 | 0.2127          | 0.919    |
| 0.2296        | 0.96  | 1500 | 0.2596          | 0.907    |
| 0.1642        | 1.28  | 2000 | 0.2009          | 0.935    |
| 0.1571        | 1.6   | 2500 | 0.2683          | 0.907    |
| 0.1523        | 1.92  | 3000 | 0.1838          | 0.948    |
| 0.1032        | 2.24  | 3500 | 0.2117          | 0.948    |
| 0.0831        | 2.56  | 4000 | 0.2541          | 0.945    |
| 0.0898        | 2.88  | 4500 | 0.3497          | 0.923    |
| 0.0644        | 3.2   | 5000 | 0.3443          | 0.927    |
| 0.0467        | 3.52  | 5500 | 0.3266          | 0.937    |
| 0.0526        | 3.84  | 6000 | 0.2849          | 0.946    |
| 0.0426        | 4.16  | 6500 | 0.3319          | 0.938    |
| 0.0253        | 4.48  | 7000 | 0.3558          | 0.932    |
| 0.0188        | 4.8   | 7500 | 0.3714          | 0.933    |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2