---
license: apache-2.0
base_model: google/bert_uncased_L-2_H-128_A-2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: kd-bertBase-bertTiny
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: sst2
      split: validation
      args: sst2
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8268348623853211
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# kd-bertBase-bertTiny

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 the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0591
- Accuracy: 0.8268

## 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: 6e-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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4776        | 1.0   | 527  | 1.1240          | 0.8062   |
| 0.8442        | 2.0   | 1054 | 1.0475          | 0.8165   |
| 0.6568        | 3.0   | 1581 | 1.0529          | 0.8131   |
| 0.5623        | 4.0   | 2108 | 1.0503          | 0.8188   |
| 0.5066        | 5.0   | 2635 | 1.0471          | 0.8303   |
| 0.4736        | 6.0   | 3162 | 1.0711          | 0.8280   |
| 0.4603        | 7.0   | 3689 | 1.0591          | 0.8268   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3