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# tiny-bert-sst2-distilled

This model was trained from scratch on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6749
- Accuracy: 0.8200

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1125        | 1.0   | 3    | 0.6731          | 0.8177   |
| 0.0984        | 2.0   | 6    | 0.6756          | 0.8188   |
| 0.1273        | 3.0   | 9    | 0.6754          | 0.8177   |
| 0.0758        | 4.0   | 12   | 0.6751          | 0.8188   |
| 0.1188        | 5.0   | 15   | 0.6754          | 0.8188   |
| 0.0936        | 6.0   | 18   | 0.6749          | 0.8200   |
| 0.0781        | 7.0   | 21   | 0.6748          | 0.8200   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["accuracy"], "model-index": [{"name": "tiny-bert-sst2-distilled", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "config": "sst2", "split": "validation", "args": "sst2"}, "metrics": [{"type": "accuracy", "value": 0.819954128440367, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard safetensors bert text-classification generated_from_trainer dataset:glue model-index autotrain_compatible endpoints_compatible region:us