---
license: apache-2.0
base_model: google/bert_uncased_L-2_H-128_A-2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tiny-bert-sst2-distilled
  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. -->

# tiny-bert-sst2-distilled

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: 1.1018
- Accuracy: 0.8211

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4646        | 1.0   | 527  | 1.1825          | 0.7867   |
| 0.8559        | 2.0   | 1054 | 1.0389          | 0.8085   |
| 0.6569        | 3.0   | 1581 | 1.0545          | 0.8222   |
| 0.5672        | 4.0   | 2108 | 1.0577          | 0.8188   |
| 0.5094        | 5.0   | 2635 | 1.0876          | 0.8211   |
| 0.4717        | 6.0   | 3162 | 1.0979          | 0.8200   |
| 0.4513        | 7.0   | 3689 | 1.1018          | 0.8211   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1