---
license: apache-2.0
base_model: google/bert_uncased_L-4_H-128_A-2
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_uncased_L-4_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: 0.7122479094933596
---

<!-- 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-128_A-2_massive

This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co./google/bert_uncased_L-4_H-128_A-2) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5917
- Accuracy: 0.7122

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8362        | 1.0   | 180  | 3.5577          | 0.2750   |
| 3.3785        | 2.0   | 360  | 3.1194          | 0.4215   |
| 3.0059        | 3.0   | 540  | 2.7843          | 0.4845   |
| 2.7219        | 4.0   | 720  | 2.5372          | 0.5273   |
| 2.4947        | 5.0   | 900  | 2.3286          | 0.5578   |
| 2.3072        | 6.0   | 1080 | 2.1582          | 0.5947   |
| 2.1494        | 7.0   | 1260 | 2.0276          | 0.6232   |
| 2.0206        | 8.0   | 1440 | 1.9108          | 0.6375   |
| 1.9207        | 9.0   | 1620 | 1.8206          | 0.6704   |
| 1.83          | 10.0  | 1800 | 1.7500          | 0.6891   |
| 1.7592        | 11.0  | 1980 | 1.6872          | 0.7004   |
| 1.7011        | 12.0  | 2160 | 1.6489          | 0.7019   |
| 1.6627        | 13.0  | 2340 | 1.6160          | 0.7093   |
| 1.6347        | 14.0  | 2520 | 1.5992          | 0.7118   |
| 1.6216        | 15.0  | 2700 | 1.5917          | 0.7122   |


### Framework versions

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