---
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
  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

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: 1.0805
- Model Preparation Time: 0.0009
- Accuracy: 0.8360

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|
| 1.2724        | 1.0   | 527  | 1.0482          | 0.0009                 | 0.8108   |
| 0.6783        | 2.0   | 1054 | 1.0651          | 0.0009                 | 0.8280   |
| 0.5164        | 3.0   | 1581 | 1.0805          | 0.0009                 | 0.8360   |
| 0.4397        | 4.0   | 2108 | 1.1196          | 0.0009                 | 0.8280   |
| 0.3887        | 5.0   | 2635 | 1.1339          | 0.0009                 | 0.8314   |
| 0.3558        | 6.0   | 3162 | 1.1385          | 0.0009                 | 0.8326   |
| 0.3397        | 7.0   | 3689 | 1.1512          | 0.0009                 | 0.8268   |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2