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

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: 0.2958
- Accuracy: 0.91

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4142        | 0.6   | 30   | 1.2653          | 0.45     |
| 0.9856        | 1.2   | 60   | 0.7754          | 0.87     |
| 0.5056        | 1.8   | 90   | 0.4413          | 0.9      |
| 0.2248        | 2.4   | 120  | 0.2984          | 0.92     |
| 0.1352        | 3.0   | 150  | 0.3265          | 0.89     |
| 0.0856        | 3.6   | 180  | 0.2958          | 0.91     |
| 0.0715        | 4.2   | 210  | 0.2611          | 0.92     |
| 0.0615        | 4.8   | 240  | 0.2738          | 0.93     |


### Framework versions

- Transformers 4.21.3
- Pytorch 1.13.0+cpu
- Datasets 2.8.0
- Tokenizers 0.12.1