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BERTForDetectingDepression-Twitter2020
Silicon23/BERTForDetectingDepression-Twitter2020
BERTForDetectingDepression-Twitter2020 is a text classification model from Silicon23. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- bert
- Access
- Public
- Created
- Jul 31, 2024
- Updated
- Aug 1, 2024
- SHA
- a311ff26
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
BERTForDetectingDepression-Twitter2020
This model is a fine-tuned version of AIMH/mental-bert-base-cased on data taken from Safa, R., Bayat, P. & Moghtader, L. Automatic detection of depression symptoms in twitter using multimodal analysis. J Supercomput (2021).. It achieves the following results on the evaluation set:
- Loss: 0.8966
- Accuracy: 0.6445
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Eval Accuracy: 0.6445
Eval Precision: 0.627281460134486
Eval Recall: 0.6690573770491803
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3.083803249747333e-05
- train_batch_size: 4
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6484 | 1.0 | 4500 | 0.6851 | 0.637 |
| 0.5904 | 2.0 | 9000 | 0.8966 | 0.6445 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- cc-by-nc-4.0
- Created
- Jul 31, 2024
- Updated
- Aug 1, 2024