---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- depression-reddit-cleaned
metrics:
- accuracy
model-index:
- name: depression-reddit-distilroberta-base
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: depression-reddit-cleaned
      type: depression-reddit-cleaned
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9786683904330963
---

<!-- 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. -->

# depression-reddit-distilroberta-base

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the depression-reddit-cleaned dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1287
- Accuracy: 0.9787

## 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: 5e-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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1792        | 0.65  | 500  | 0.1206          | 0.9709   |
| 0.1074        | 1.29  | 1000 | 0.1155          | 0.9716   |
| 0.0649        | 1.94  | 1500 | 0.0980          | 0.9825   |
| 0.0243        | 2.59  | 2000 | 0.1287          | 0.9787   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3