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# tinybert-TG-HS-HX-parentpretrained

This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1937
- Accuracy: 0.8230

## 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: 5.2898091511494136e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1819        | 1.0   | 197  | 0.1923          | 0.8227   |
| 0.1791        | 2.0   | 394  | 0.1922          | 0.8223   |
| 0.1772        | 3.0   | 591  | 0.1950          | 0.8143   |
| 0.1761        | 4.0   | 788  | 0.1932          | 0.8239   |
| 0.1756        | 5.0   | 985  | 0.1932          | 0.8234   |
| 0.1752        | 6.0   | 1182 | 0.1939          | 0.8242   |
| 0.1759        | 7.0   | 1379 | 0.1937          | 0.8230   |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/bert_uncased_L-4_H-256_A-4", "model-index": [{"name": "tinybert-TG-HS-HX-parentpretrained", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:google/bert_uncased_L-4_H-256_A-4 license:apache-2.0 autotrain_compatible endpoints_compatible region:us