---
license: apache-2.0
base_model: google/bert_uncased_L-4_H-768_A-12
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_uncased_L-4_H-768_A-12_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: 0.8898180029513035
---

<!-- 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_uncased_L-4_H-768_A-12_massive

This model is a fine-tuned version of [google/bert_uncased_L-4_H-768_A-12](https://huggingface.co/google/bert_uncased_L-4_H-768_A-12) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5747
- Accuracy: 0.8898

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1636        | 1.0   | 180  | 0.9552          | 0.7983   |
| 0.7696        | 2.0   | 360  | 0.5934          | 0.8539   |
| 0.4303        | 3.0   | 540  | 0.4996          | 0.8721   |
| 0.2708        | 4.0   | 720  | 0.4900          | 0.8780   |
| 0.1756        | 5.0   | 900  | 0.4886          | 0.8780   |
| 0.113         | 6.0   | 1080 | 0.5020          | 0.8829   |
| 0.076         | 7.0   | 1260 | 0.5211          | 0.8810   |
| 0.0517        | 8.0   | 1440 | 0.5452          | 0.8864   |
| 0.035         | 9.0   | 1620 | 0.5516          | 0.8883   |
| 0.026         | 10.0  | 1800 | 0.5652          | 0.8864   |
| 0.0193        | 11.0  | 1980 | 0.5696          | 0.8869   |
| 0.0156        | 12.0  | 2160 | 0.5592          | 0.8888   |
| 0.0134        | 13.0  | 2340 | 0.5762          | 0.8893   |
| 0.0103        | 14.0  | 2520 | 0.5726          | 0.8883   |
| 0.0107        | 15.0  | 2700 | 0.5747          | 0.8898   |


### Framework versions

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