---
license: apache-2.0
base_model: google/bert_uncased_L-4_H-256_A-4
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_uncased_L-4_H-256_A-4_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: 0.8362026561731432
---

<!-- 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-256_A-4_massive

This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7252
- Accuracy: 0.8362

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.5031        | 1.0   | 180  | 2.8542          | 0.4437   |
| 2.5403        | 2.0   | 360  | 2.0782          | 0.6394   |
| 1.928         | 3.0   | 540  | 1.6213          | 0.7118   |
| 1.542         | 4.0   | 720  | 1.3355          | 0.7526   |
| 1.2771        | 5.0   | 900  | 1.1556          | 0.7801   |
| 1.0852        | 6.0   | 1080 | 1.0223          | 0.7964   |
| 0.939         | 7.0   | 1260 | 0.9331          | 0.8047   |
| 0.8352        | 8.0   | 1440 | 0.8670          | 0.8146   |
| 0.7522        | 9.0   | 1620 | 0.8184          | 0.8190   |
| 0.6847        | 10.0  | 1800 | 0.7887          | 0.8254   |
| 0.6369        | 11.0  | 1980 | 0.7578          | 0.8254   |
| 0.5943        | 12.0  | 2160 | 0.7413          | 0.8323   |
| 0.5652        | 13.0  | 2340 | 0.7288          | 0.8328   |
| 0.5486        | 14.0  | 2520 | 0.7252          | 0.8362   |
| 0.5394        | 15.0  | 2700 | 0.7190          | 0.8357   |


### Framework versions

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