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---
base_model: gokuls/bert_12_layer_model_v4_complete_training_48
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v4_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: 0.839153959665519
---

<!-- 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_v4_48_massive

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v4_complete_training_48](https://huggingface.co/gokuls/bert_12_layer_model_v4_complete_training_48) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9030
- Accuracy: 0.8392

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.1903        | 1.0   | 180  | 2.2860          | 0.4048   |
| 1.81          | 2.0   | 360  | 1.3971          | 0.6134   |
| 1.1787        | 3.0   | 540  | 1.0028          | 0.7270   |
| 0.8518        | 4.0   | 720  | 0.8662          | 0.7718   |
| 0.6633        | 5.0   | 900  | 0.8229          | 0.7885   |
| 0.5208        | 6.0   | 1080 | 0.8214          | 0.8037   |
| 0.4179        | 7.0   | 1260 | 0.7887          | 0.8008   |
| 0.3308        | 8.0   | 1440 | 0.7357          | 0.8293   |
| 0.2518        | 9.0   | 1620 | 0.7840          | 0.8195   |
| 0.1997        | 10.0  | 1800 | 0.7644          | 0.8283   |
| 0.1472        | 11.0  | 1980 | 0.8304          | 0.8318   |
| 0.1122        | 12.0  | 2160 | 0.8461          | 0.8347   |
| 0.0816        | 13.0  | 2340 | 0.8959          | 0.8328   |
| 0.0601        | 14.0  | 2520 | 0.8811          | 0.8382   |
| 0.0401        | 15.0  | 2700 | 0.9030          | 0.8392   |


### Framework versions

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