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tiny-bert-sst2-distilled
alisonip1/tiny-bert-sst2-distilled
tiny-bert-sst2-distilled is a machine learning model from alisonip1. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Dec 5, 2025
- Updated
- Dec 9, 2025
- SHA
- b836b359
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. -->
tiny-bert-sst2-distilled
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0578
- Accuracy: 0.8406
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: 0.0009127050926907179
- train_batch_size: 1024
- eval_batch_size: 1024
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8929 | 1.0 | 66 | 0.9213 | 0.8245 |
| 0.4128 | 2.0 | 132 | 0.9446 | 0.8337 |
| 0.2886 | 3.0 | 198 | 0.9660 | 0.8406 |
| 0.2309 | 4.0 | 264 | 1.0578 | 0.8406 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.16.1
- Tokenizers 0.13.3
- Type
- bert
- License
- apache-2.0
- Created
- Dec 5, 2025
- Updated
- Dec 9, 2025