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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- depression-reddit-cleaned
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metrics:
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- accuracy
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model-index:
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- name: depression-reddit-distilroberta-base
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: depression-reddit-cleaned
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type: depression-reddit-cleaned
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9831932773109243
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# depression-reddit-distilroberta-base
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This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the depression-reddit-cleaned dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0948
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- Accuracy: 0.9832
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.1807 | 0.65 | 500 | 0.1087 | 0.9683 |
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| 0.1227 | 1.29 | 1000 | 0.1002 | 0.9793 |
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| 0.0663 | 1.94 | 1500 | 0.1097 | 0.9806 |
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| 0.031 | 2.59 | 2000 | 0.0948 | 0.9832 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.0
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- Tokenizers 0.13.3
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