---
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