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stock-classifier
hkufyp2024/stock-classifier
stock-classifier is a text classification model from hkufyp2024. 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
- distilbert
- Access
- Public
- Created
- Apr 22, 2024
- Updated
- Apr 26, 2024
- SHA
- ae2691a9
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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. -->
stock-classifier
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0048
- Accuracy: 0.9984
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.3667 | 1.0 | 2844 | 4.5999 | 0.5886 |
| 1.8303 | 2.0 | 5688 | 1.3704 | 0.9620 |
| 0.2384 | 3.0 | 8532 | 0.1371 | 0.9937 |
| 0.0442 | 4.0 | 11376 | 0.0178 | 0.9953 |
| 0.0188 | 5.0 | 14220 | 0.0060 | 0.9984 |
| 0.0072 | 6.0 | 17064 | 0.0061 | 0.9984 |
| 0.0076 | 7.0 | 19908 | 0.0033 | 0.9984 |
| 0.0045 | 8.0 | 22752 | 0.0046 | 0.9984 |
| 0.0044 | 9.0 | 25596 | 0.0048 | 0.9984 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Apr 22, 2024
- Updated
- Apr 26, 2024