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---
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
---
<!-- 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: 0.0948
- 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
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