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depression_tweet
ziq/depression_tweet
depression_tweet is a text classification model from ziq. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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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. -->
depression_tweet
This model is a fine-tuned version of microsoft/xtremedistil-l6-h384-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1606
- Accuracy: 0.9565
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: 3e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 216 | 0.1369 | 0.9497 |
| No log | 2.0 | 432 | 0.1588 | 0.9552 |
| 0.0514 | 3.0 | 648 | 0.1647 | 0.9562 |
| 0.0514 | 4.0 | 864 | 0.1606 | 0.9565 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Jun 6, 2022
- Updated
- Jun 20, 2023