---
license: apache-2.0
base_model: google/bert_uncased_L-6_H-128_A-2
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_uncased_L-6_H-128_A-2_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: 0.7314313821938022
---

<!-- 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-128_A-2_massive

This model is a fine-tuned version of [google/bert_uncased_L-6_H-128_A-2](https://huggingface.co/google/bert_uncased_L-6_H-128_A-2) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5439
- Accuracy: 0.7314

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8348        | 1.0   | 180  | 3.5466          | 0.3192   |
| 3.3738        | 2.0   | 360  | 3.1057          | 0.4407   |
| 2.9882        | 3.0   | 540  | 2.7502          | 0.5140   |
| 2.6778        | 4.0   | 720  | 2.4684          | 0.5789   |
| 2.4276        | 5.0   | 900  | 2.2516          | 0.6158   |
| 2.2242        | 6.0   | 1080 | 2.0764          | 0.6419   |
| 2.0619        | 7.0   | 1260 | 1.9388          | 0.6827   |
| 1.932         | 8.0   | 1440 | 1.8294          | 0.6827   |
| 1.8283        | 9.0   | 1620 | 1.7395          | 0.6975   |
| 1.7411        | 10.0  | 1800 | 1.6747          | 0.7118   |
| 1.6698        | 11.0  | 1980 | 1.6142          | 0.7137   |
| 1.6176        | 12.0  | 2160 | 1.5737          | 0.7231   |
| 1.5796        | 13.0  | 2340 | 1.5439          | 0.7314   |
| 1.5509        | 14.0  | 2520 | 1.5284          | 0.7300   |
| 1.5409        | 15.0  | 2700 | 1.5226          | 0.7285   |


### Framework versions

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