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

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: 0.9967
- Accuracy: 0.9032

## 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: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3072        | 1.0   | 5250  | 0.2747          | 0.8940   |
| 0.2381        | 2.0   | 10500 | 0.2871          | 0.8986   |
| 0.1858        | 3.0   | 15750 | 0.3444          | 0.8996   |
| 0.1385        | 4.0   | 21000 | 0.4799          | 0.8937   |
| 0.1057        | 5.0   | 26250 | 0.5324          | 0.8961   |
| 0.0779        | 6.0   | 31500 | 0.6222          | 0.8969   |
| 0.0654        | 7.0   | 36750 | 0.6665          | 0.8968   |
| 0.046         | 8.0   | 42000 | 0.7111          | 0.8989   |
| 0.0384        | 9.0   | 47250 | 0.7815          | 0.8987   |
| 0.0348        | 10.0  | 52500 | 0.8023          | 0.9029   |
| 0.0224        | 11.0  | 57750 | 0.8676          | 0.9011   |
| 0.0172        | 12.0  | 63000 | 0.8881          | 0.8999   |
| 0.0068        | 13.0  | 68250 | 0.9122          | 0.9025   |
| 0.0032        | 14.0  | 73500 | 0.9938          | 0.9005   |
| 0.0071        | 15.0  | 78750 | 0.9967          | 0.9032   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3