---
license: apache-2.0
base_model: google/bert_uncased_L-2_H-512_A-8
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_uncased_L-2_H-512_A-8_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: 0.8740777176586325
---

<!-- 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-2_H-512_A-8_massive

This model is a fine-tuned version of [google/bert_uncased_L-2_H-512_A-8](https://huggingface.co/google/bert_uncased_L-2_H-512_A-8) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5162
- Accuracy: 0.8741

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.9188        | 1.0   | 180  | 1.8187          | 0.6085   |
| 1.5237        | 2.0   | 360  | 1.0972          | 0.7585   |
| 0.9995        | 3.0   | 540  | 0.8257          | 0.7978   |
| 0.7371        | 4.0   | 720  | 0.6883          | 0.8318   |
| 0.5734        | 5.0   | 900  | 0.6198          | 0.8455   |
| 0.4599        | 6.0   | 1080 | 0.5870          | 0.8569   |
| 0.3835        | 7.0   | 1260 | 0.5654          | 0.8574   |
| 0.3262        | 8.0   | 1440 | 0.5414          | 0.8652   |
| 0.279         | 9.0   | 1620 | 0.5282          | 0.8697   |
| 0.2435        | 10.0  | 1800 | 0.5281          | 0.8677   |
| 0.2199        | 11.0  | 1980 | 0.5156          | 0.8697   |
| 0.1999        | 12.0  | 2160 | 0.5162          | 0.8741   |
| 0.1824        | 13.0  | 2340 | 0.5224          | 0.8736   |
| 0.1712        | 14.0  | 2520 | 0.5223          | 0.8731   |
| 0.1627        | 15.0  | 2700 | 0.5206          | 0.8716   |


### Framework versions

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