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tiny-bert-sst2-distilled_qat_test
jysh1023/tiny-bert-sst2-distilled_qat_test
tiny-bert-sst2-distilled_qat_test is a text classification model from jysh1023. 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
- Nov 18, 2023
- Updated
- Nov 18, 2023
- SHA
- b598899e
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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_qat_test
This model is a fine-tuned version of jysh1023/tiny-bert-sst2-distilled_qat_test on the glue dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.1017
- eval_accuracy: 0.7775
- eval_runtime: 0.1618
- eval_samples_per_second: 5390.016
- eval_steps_per_second: 43.268
- epoch: 1.0
- step: 527
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: 4.3501969464061515e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Nov 18, 2023
- Updated
- Nov 18, 2023