Downloads · 30 days
4.3K
1% of all-time downloads
tiny-bert-sst2-distilled
philschmid/tiny-bert-sst2-distilled
tiny-bert-sst2-distilled is a text classification model from philschmid. 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. --
All-time downloads
459K
Public
Repo size
3.8 GB
Likes
2
Public
Repo makeup
Click a slice to open those files.
.bin17.6 MB · 96%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jan 31, 2022
- SHA
- 874eb285
Try a prompt
Datasets
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 the glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.7305
- Accuracy: 0.8326
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: 0.0007199555649276667
- 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: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.77 | 1.0 | 66 | 1.6939 | 0.8165 |
| 0.729 | 2.0 | 132 | 1.5090 | 0.8326 |
| 0.5242 | 3.0 | 198 | 1.5369 | 0.8257 |
| 0.4017 | 4.0 | 264 | 1.7025 | 0.8326 |
| 0.327 | 5.0 | 330 | 1.6743 | 0.8245 |
| 0.2749 | 6.0 | 396 | 1.7305 | 0.8337 |
| 0.2521 | 7.0 | 462 | 1.7305 | 0.8326 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.9.1
- Datasets 1.15.1
- Tokenizers 0.10.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Hf Inference
- live
- Created
- Mar 2, 2022
- Updated
- Jan 31, 2022