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sbert_imdb
Siki-77/sbert_imdb
sbert_imdb is a text classification model from Siki-77. 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
- mpnet
- Access
- Public
- Created
- Jul 18, 2024
- Updated
- Jul 18, 2024
- SHA
- 404b5506
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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. -->
sbert_imdb
This model is a fine-tuned version of sentence-transformers/all-mpnet-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2169
- Accuracy: 0.9532
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.1719 | 0.9997 | 1562 | 0.1483 | 0.9469 |
| 0.1195 | 2.0 | 3125 | 0.1756 | 0.9521 |
| 0.0765 | 2.9997 | 4687 | 0.2224 | 0.9468 |
| 0.0421 | 4.0 | 6250 | 0.2169 | 0.9532 |
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
- mpnet
- License
- apache-2.0
- Created
- Jul 18, 2024
- Updated
- Jul 18, 2024