---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-1k
  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-1k

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0986
- Accuracy: 0.3333

## 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-07
- 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: 25

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 1.0989        | 1.0   | 6000   | 1.0986          | 0.3333   |
| 1.0993        | 2.0   | 12000  | 1.0986          | 0.3333   |
| 1.0992        | 3.0   | 18000  | 1.0986          | 0.3333   |
| 1.0993        | 4.0   | 24000  | 1.0986          | 0.3333   |
| 1.0985        | 5.0   | 30000  | 1.0986          | 0.3333   |
| 1.0988        | 6.0   | 36000  | 1.0986          | 0.3333   |
| 1.0993        | 7.0   | 42000  | 1.0986          | 0.3333   |
| 1.0983        | 8.0   | 48000  | 1.0986          | 0.3333   |
| 1.0983        | 9.0   | 54000  | 1.0986          | 0.3333   |
| 1.0982        | 10.0  | 60000  | 1.0986          | 0.3333   |
| 1.0986        | 11.0  | 66000  | 1.0986          | 0.3333   |
| 1.0985        | 12.0  | 72000  | 1.0986          | 0.3333   |
| 1.0983        | 13.0  | 78000  | 1.0986          | 0.3333   |
| 1.0987        | 14.0  | 84000  | 1.0986          | 0.3333   |
| 1.0992        | 15.0  | 90000  | 1.0986          | 0.3333   |
| 1.099         | 16.0  | 96000  | 1.0986          | 0.3333   |
| 1.0991        | 17.0  | 102000 | 1.0986          | 0.3333   |
| 1.0982        | 18.0  | 108000 | 1.0986          | 0.3333   |
| 1.0989        | 19.0  | 114000 | 1.0986          | 0.3333   |
| 1.099         | 20.0  | 120000 | 1.0986          | 0.3333   |
| 1.0991        | 21.0  | 126000 | 1.0986          | 0.3333   |
| 1.099         | 22.0  | 132000 | 1.0986          | 0.3333   |
| 1.099         | 23.0  | 138000 | 1.0986          | 0.3333   |
| 1.0984        | 24.0  | 144000 | 1.0986          | 0.3333   |
| 1.0985        | 25.0  | 150000 | 1.0986          | 0.3333   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.0.0+cu117
- Datasets 2.19.0
- Tokenizers 0.19.1