---
base_model: gokuls/bert_12_layer_model_v3_complete_training_48
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v3_48_massive
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: massive
      type: massive
      config: en-US
      split: validation
      args: en-US
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8607968519429414
---

<!-- 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. -->

# bert_12_layer_model_v3_48_massive

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v3_complete_training_48](https://huggingface.co/gokuls/bert_12_layer_model_v3_complete_training_48) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9214
- Accuracy: 0.8608

## 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: 33
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7608        | 1.0   | 180  | 0.9351          | 0.7482   |
| 0.8417        | 2.0   | 360  | 0.8314          | 0.7841   |
| 0.6057        | 3.0   | 540  | 0.7307          | 0.8160   |
| 0.4715        | 4.0   | 720  | 0.6995          | 0.8382   |
| 0.3766        | 5.0   | 900  | 0.7602          | 0.8273   |
| 0.2933        | 6.0   | 1080 | 0.7537          | 0.8357   |
| 0.2321        | 7.0   | 1260 | 0.7966          | 0.8426   |
| 0.1873        | 8.0   | 1440 | 0.8015          | 0.8396   |
| 0.1447        | 9.0   | 1620 | 0.8281          | 0.8392   |
| 0.1079        | 10.0  | 1800 | 0.8665          | 0.8446   |
| 0.0781        | 11.0  | 1980 | 0.8758          | 0.8500   |
| 0.0573        | 12.0  | 2160 | 0.8646          | 0.8515   |
| 0.0383        | 13.0  | 2340 | 0.9121          | 0.8603   |
| 0.024         | 14.0  | 2520 | 0.8963          | 0.8593   |
| 0.015         | 15.0  | 2700 | 0.9214          | 0.8608   |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1