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TinyBERT-distillation-clinc
Pi-Marie/TinyBERT-distillation-clinc
TinyBERT-distillation-clinc is a text classification model from Pi-Marie. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Sep 29, 2025
- Updated
- Sep 29, 2025
- SHA
- 8833897e
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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. -->
TinyBERT-distillation-clinc
This model is a fine-tuned version of huawei-noah/TinyBERT_General_4L_312D on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.1571
- Accuracy: 0.1926
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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 4.7679 | 0.1123 |
| 4.839 | 2.0 | 636 | 4.4874 | 0.1084 |
| 4.839 | 3.0 | 954 | 4.3043 | 0.1358 |
| 4.426 | 4.0 | 1272 | 4.1943 | 0.1765 |
| 4.2081 | 5.0 | 1590 | 4.1571 | 0.1926 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Sep 29, 2025
- Updated
- Sep 29, 2025