
<!-- 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. -->

# thesis

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: 2.7609
- Accuracy: 0.7546

## 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: 3.0969456495664865e-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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.5143        | 1.0   | 527  | 2.7609          | 0.7546   |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.12.0
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/bert_uncased_L-2_H-128_A-2", "model-index": [{"name": "thesis", "results": []}]}
transformers tensorboard safetensors phi text-classification generated_from_trainer custom_code base_model:google/bert_uncased_L-2_H-128_A-2 license:apache-2.0 autotrain_compatible endpoints_compatible region:us