metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - depression-reddit-cleaned
metrics:
  - accuracy
widget:
  - text:
      - >-
        i just found out my boyfriend is depressed i really want to be there for
        him but i feel like i ve only been saying the wrong thing how can i be
        there for him help him and see him get better i m worried it will
        continue to the point it will consume him i can already see his
        personality changing and i m scared for the future what thing can i say
        or do to comfort or help
    example_title: depression
  - text:
      - >-
        i m getting more and more people asking where they can buy the ambients
        album simple answer is quot not yet quot it ll be on itunes eventually
    example_title: not_depression
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: 0.9831932773109243

depression-reddit-distilroberta-base

This model is a fine-tuned version of distilroberta-base on the depression-reddit-cleaned dataset. It achieves the following results on the evaluation set:

Loss: 0.0948
Accuracy: 0.9832

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
0.1807	0.65	500	0.1087	0.9683
0.1227	1.29	1000	0.1002	0.9793
0.0663	1.94	1500	0.1097	0.9806
0.031	2.59	2000	0.0948	0.9832

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.13.0
Tokenizers 0.13.3