---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v1_complete_training_new_wt_init_96
  results: []
---

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# bert_12_layer_model_v1_complete_training_new_wt_init_96

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_72](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_72) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2871
- Accuracy: 0.5730

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 2.5078        | 0.08  | 10000  | 2.4110          | 0.5558   |
| 2.4913        | 0.16  | 20000  | 2.3958          | 0.5579   |
| 2.4725        | 0.25  | 30000  | 2.3794          | 0.5603   |
| 2.4698        | 0.33  | 40000  | 2.3644          | 0.5623   |
| 2.4431        | 0.41  | 50000  | 2.3489          | 0.5645   |
| 2.4345        | 0.49  | 60000  | 2.3352          | 0.5665   |
| 2.412         | 0.57  | 70000  | 2.3221          | 0.5683   |
| 2.3999        | 0.66  | 80000  | 2.3079          | 0.5697   |
| 2.3844        | 0.74  | 90000  | 2.2933          | 0.5713   |
| 2.3732        | 0.82  | 100000 | 2.2871          | 0.5730   |


### Framework versions

- Transformers 4.30.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3