---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: tiny-bert-sst2-distilled-model
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      args: sst2
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.838302752293578
---

<!-- 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-model

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: 1.2592
- Accuracy: 0.8383

## 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: 16
- eval_batch_size: 16
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5303        | 1.0   | 4210  | 1.2542          | 0.8222   |
| 0.4503        | 2.0   | 8420  | 1.1260          | 0.8211   |
| 0.3689        | 3.0   | 12630 | 1.2325          | 0.8234   |
| 0.3122        | 4.0   | 16840 | 1.2533          | 0.8337   |
| 0.2764        | 5.0   | 21050 | 1.2726          | 0.8337   |
| 0.254         | 6.0   | 25260 | 1.2609          | 0.8337   |
| 0.2358        | 7.0   | 29470 | 1.2592          | 0.8383   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.10.1+cu113
- Datasets 1.15.1
- Tokenizers 0.12.1