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sbert_imdb_fast
Siki-77/sbert_imdb_fast
sbert_imdb_fast 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
- bert
- Access
- Public
- Created
- Jul 18, 2024
- Updated
- Jul 18, 2024
- SHA
- aa214e1b
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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_fast
This model is a fine-tuned version of sentence-transformers/all-MiniLM-L6-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2458
- Accuracy: 0.9256
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.3444 | 1.0 | 781 | 0.2201 | 0.9110 |
| 0.2001 | 2.0 | 1563 | 0.2423 | 0.9058 |
| 0.1655 | 3.0 | 2344 | 0.2117 | 0.9247 |
| 0.1292 | 4.0 | 3126 | 0.2203 | 0.9253 |
| 0.1115 | 5.0 | 3905 | 0.2458 | 0.9256 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jul 18, 2024
- Updated
- Jul 18, 2024