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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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metrics: |
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- accuracy |
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widget: |
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- text: "It's in the back of my mind. I'm not sure I'll be ok. Not sure I can deal with this. I'll try...I will try. Even though it's hard to see the point. But...this still isn't off the table." |
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model-index: |
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- name: distilroberta-base-finetuned-suicide-depression |
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results: [] |
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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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# distilroberta-base-finetuned-suicide-depression |
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This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6622 |
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- Accuracy: 0.7158 |
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## Model description |
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Just a **POC** of a Transformer fine-tuned on [SDCNL](https://github.com/ayaanzhaque/SDCNL) dataset for suicide (label 1) or depression (label 0) detection in tweets. |
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**DO NOT use it in production** |
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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: 2e-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: 5 |
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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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| No log | 1.0 | 214 | 0.6204 | 0.6632 | |
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| No log | 2.0 | 428 | 0.6622 | 0.7158 | |
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| 0.5244 | 3.0 | 642 | 0.7312 | 0.6684 | |
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| 0.5244 | 4.0 | 856 | 0.9711 | 0.7105 | |
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| 0.2876 | 5.0 | 1070 | 1.1620 | 0.7 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.13.0 |
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- Tokenizers 0.10.3 |
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