transformers pytorch bert text-classification generated_from_trainer dataset:massive base_model:google/bert_uncased_L-8_H-128_A-2 base_model:finetune:google/bert_uncased_L-8_H-128_A-2 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google/bert_uncased_L-8_H-128_A-2
datasets:
- massive
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert_uncased_L-8_H-128_A-2_massive
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: massive
      type: massive
      config: en-US
      split: validation
      args: en-US
    metrics:
    - type: accuracy
      value: 0.7333989178553861
      name: Accuracy
---

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# bert_uncased_L-8_H-128_A-2_massive

This model is a fine-tuned version of [google/bert_uncased_L-8_H-128_A-2](https://huggingface.co/google/bert_uncased_L-8_H-128_A-2) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4687
- Accuracy: 0.7334

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.7982        | 1.0   | 180  | 3.4791          | 0.3335   |
| 3.287         | 2.0   | 360  | 3.0244          | 0.4299   |
| 2.8916        | 3.0   | 540  | 2.6675          | 0.5047   |
| 2.5836        | 4.0   | 720  | 2.3965          | 0.5839   |
| 2.3397        | 5.0   | 900  | 2.1824          | 0.6291   |
| 2.1423        | 6.0   | 1080 | 2.0132          | 0.6680   |
| 1.9823        | 7.0   | 1260 | 1.8773          | 0.6872   |
| 1.8543        | 8.0   | 1440 | 1.7682          | 0.6940   |
| 1.7528        | 9.0   | 1620 | 1.6818          | 0.7049   |
| 1.6612        | 10.0  | 1800 | 1.6191          | 0.7118   |
| 1.595         | 11.0  | 1980 | 1.5608          | 0.7226   |
| 1.5406        | 12.0  | 2160 | 1.5231          | 0.7270   |
| 1.4997        | 13.0  | 2340 | 1.4922          | 0.7309   |
| 1.4719        | 14.0  | 2520 | 1.4760          | 0.7329   |
| 1.4595        | 15.0  | 2700 | 1.4687          | 0.7334   |


### Framework versions

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