---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased
  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-base-uncased

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0002

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.0273        | 0.2907  | 500   | 0.0062          |
| 0.0049        | 0.5814  | 1000  | 0.0024          |
| 0.0033        | 0.8721  | 1500  | 0.0020          |
| 0.0014        | 1.1628  | 2000  | 0.0009          |
| 0.001         | 1.4535  | 2500  | 0.0007          |
| 0.0008        | 1.7442  | 3000  | 0.0009          |
| 0.0011        | 2.0349  | 3500  | 0.0011          |
| 0.0003        | 2.3256  | 4000  | 0.0012          |
| 0.0008        | 2.6163  | 4500  | 0.0008          |
| 0.0006        | 2.9070  | 5000  | 0.0010          |
| 0.0006        | 3.1977  | 5500  | 0.0009          |
| 0.0002        | 3.4884  | 6000  | 0.0008          |
| 0.0005        | 3.7791  | 6500  | 0.0005          |
| 0.0003        | 4.0698  | 7000  | 0.0005          |
| 0.0002        | 4.3605  | 7500  | 0.0003          |
| 0.0004        | 4.6512  | 8000  | 0.0015          |
| 0.0004        | 4.9419  | 8500  | 0.0008          |
| 0.0002        | 5.2326  | 9000  | 0.0002          |
| 0.0003        | 5.5233  | 9500  | 0.0003          |
| 0.0002        | 5.8140  | 10000 | 0.0002          |
| 0.0002        | 6.1047  | 10500 | 0.0003          |
| 0.0001        | 6.3953  | 11000 | 0.0002          |
| 0.0001        | 6.6860  | 11500 | 0.0002          |
| 0.0001        | 6.9767  | 12000 | 0.0003          |
| 0.0           | 7.2674  | 12500 | 0.0002          |
| 0.0           | 7.5581  | 13000 | 0.0009          |
| 0.0001        | 7.8488  | 13500 | 0.0005          |
| 0.0002        | 8.1395  | 14000 | 0.0007          |
| 0.0001        | 8.4302  | 14500 | 0.0007          |
| 0.0001        | 8.7209  | 15000 | 0.0006          |
| 0.0001        | 9.0116  | 15500 | 0.0005          |
| 0.0           | 9.3023  | 16000 | 0.0007          |
| 0.0001        | 9.5930  | 16500 | 0.0005          |
| 0.0003        | 9.8837  | 17000 | 0.0004          |
| 0.0           | 10.1744 | 17500 | 0.0004          |
| 0.0002        | 10.4651 | 18000 | 0.0003          |
| 0.0           | 10.7558 | 18500 | 0.0003          |
| 0.0           | 11.0465 | 19000 | 0.0004          |
| 0.0           | 11.3372 | 19500 | 0.0004          |
| 0.0           | 11.6279 | 20000 | 0.0002          |
| 0.0           | 11.9186 | 20500 | 0.0002          |
| 0.0           | 12.2093 | 21000 | 0.0003          |
| 0.0           | 12.5    | 21500 | 0.0003          |
| 0.0           | 12.7907 | 22000 | 0.0004          |
| 0.0           | 13.0814 | 22500 | 0.0002          |
| 0.0001        | 13.3721 | 23000 | 0.0002          |
| 0.0001        | 13.6628 | 23500 | 0.0002          |
| 0.0           | 13.9535 | 24000 | 0.0002          |
| 0.0           | 14.2442 | 24500 | 0.0002          |
| 0.0           | 14.5349 | 25000 | 0.0002          |
| 0.0           | 14.8256 | 25500 | 0.0002          |


### Framework versions

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