---
license: apache-2.0
base_model: google/bert_uncased_L-6_H-768_A-12
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_uncased_L-6_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: 0.8888342351205115
---

<!-- 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-6_H-768_A-12_massive

This model is a fine-tuned version of [google/bert_uncased_L-6_H-768_A-12](https://huggingface.co./google/bert_uncased_L-6_H-768_A-12) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5459
- Accuracy: 0.8888

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0422        | 1.0   | 180  | 0.8433          | 0.8160   |
| 0.6599        | 2.0   | 360  | 0.5532          | 0.8618   |
| 0.3564        | 3.0   | 540  | 0.5180          | 0.8701   |
| 0.212         | 4.0   | 720  | 0.4955          | 0.8805   |
| 0.1358        | 5.0   | 900  | 0.5076          | 0.8844   |
| 0.0859        | 6.0   | 1080 | 0.5193          | 0.8864   |
| 0.059         | 7.0   | 1260 | 0.5459          | 0.8888   |
| 0.038         | 8.0   | 1440 | 0.5811          | 0.8834   |
| 0.0255        | 9.0   | 1620 | 0.5875          | 0.8849   |
| 0.0171        | 10.0  | 1800 | 0.5881          | 0.8834   |
| 0.0122        | 11.0  | 1980 | 0.6051          | 0.8829   |
| 0.0086        | 12.0  | 2160 | 0.6117          | 0.8879   |
| 0.007         | 13.0  | 2340 | 0.6032          | 0.8864   |
| 0.006         | 14.0  | 2520 | 0.6112          | 0.8824   |
| 0.0055        | 15.0  | 2700 | 0.6130          | 0.8844   |


### Framework versions

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