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bert-base-uncased-detect-depression-stage-one
hoanghoavienvo/bert-base-uncased-detect-depression-stage-one
bert-base-uncased-detect-depression-stage-one is a text classification model from hoanghoavienvo. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Jul 9, 2023
- Updated
- Jul 9, 2023
- SHA
- 111cc717
Try a prompt
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. -->
bert-base-uncased-detect-depression-stage-one
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4151
- Accuracy: 0.674
- F1: 0.7530
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6185 | 1.0 | 751 | 0.5223 | 0.762 | 0.8260 |
| 0.5394 | 2.0 | 1502 | 0.5958 | 0.692 | 0.7488 |
| 0.4387 | 3.0 | 2253 | 0.6742 | 0.706 | 0.7885 |
| 0.3157 | 4.0 | 3004 | 1.1284 | 0.696 | 0.7768 |
| 0.1794 | 5.0 | 3755 | 1.4151 | 0.674 | 0.7530 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jul 9, 2023
- Updated
- Jul 9, 2023