---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v1_complete_training_new_wt_init_48
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert_12_layer_model_v1_complete_training_new_wt_init_48

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: 2.6168
- Accuracy: 0.5281

## 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: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 6.4172        | 0.08  | 10000  | 6.3664          | 0.1317   |
| 6.1014        | 0.16  | 20000  | 6.0532          | 0.1497   |
| 5.8255        | 0.25  | 30000  | 5.7466          | 0.1656   |
| 5.0543        | 0.33  | 40000  | 4.7539          | 0.2752   |
| 4.1669        | 0.41  | 50000  | 3.8568          | 0.3739   |
| 3.7259        | 0.49  | 60000  | 3.4751          | 0.4215   |
| 3.4547        | 0.57  | 70000  | 3.2615          | 0.4469   |
| 3.2968        | 0.66  | 80000  | 3.1250          | 0.4638   |
| 3.1805        | 0.74  | 90000  | 3.0246          | 0.4760   |
| 3.0963        | 0.82  | 100000 | 2.9491          | 0.4858   |
| 3.0238        | 0.9   | 110000 | 2.8874          | 0.4933   |
| 2.9729        | 0.98  | 120000 | 2.8317          | 0.5003   |
| 2.9156        | 1.07  | 130000 | 2.7824          | 0.5063   |
| 2.8784        | 1.15  | 140000 | 2.7434          | 0.5111   |
| 2.8333        | 1.23  | 150000 | 2.7081          | 0.5164   |
| 2.8043        | 1.31  | 160000 | 2.6730          | 0.5205   |
| 2.7646        | 1.39  | 170000 | 2.6436          | 0.5248   |
| 2.7403        | 1.47  | 180000 | 2.6168          | 0.5281   |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3