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library_name: transformers
license: apache-2.0
base_model: google/bert_uncased_L-2_H-128_A-2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_distillation_tiny
results: []
---
<!-- 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. -->
# bert_distillation_tiny
This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4804
- Model Preparation Time: 0.0009
- Accuracy: 0.8303
## 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 2023
- 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: 7
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|
| 0.4157 | 1.0 | 527 | 0.4127 | 0.0009 | 0.8131 |
| 0.2693 | 2.0 | 1054 | 0.4429 | 0.0009 | 0.8211 |
| 0.2189 | 3.0 | 1581 | 0.4804 | 0.0009 | 0.8303 |
| 0.1907 | 4.0 | 2108 | 0.4995 | 0.0009 | 0.8200 |
| 0.1712 | 5.0 | 2635 | 0.5311 | 0.0009 | 0.8165 |
| 0.1597 | 6.0 | 3162 | 0.5561 | 0.0009 | 0.8131 |
| 0.1536 | 7.0 | 3689 | 0.5604 | 0.0009 | 0.8142 |
### Framework versions
- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
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