---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v1
  results: []
---

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# bert_12_layer_model_v1

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1713
- Accuracy: 0.5905

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 6.293         | 1.0   | 22886  | 5.6395          | 0.1723   |
| 3.7477        | 2.0   | 45772  | 2.6625          | 0.5252   |
| 2.5641        | 3.0   | 68658  | 2.3431          | 0.5673   |
| 2.3563        | 4.0   | 91544  | 2.2188          | 0.5839   |
| 2.2692        | 5.0   | 114430 | 2.1713          | 0.5905   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.0
- Tokenizers 0.13.2