transformers pytorch bert text-classification generated_from_trainer dataset:massive base_model:google/bert_uncased_L-2_H-768_A-12 base_model:finetune:google/bert_uncased_L-2_H-768_A-12 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google/bert_uncased_L-2_H-768_A-12
datasets:
- massive
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert_uncased_L-2_H-768_A-12_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: 0.8745696015740285
      name: Accuracy
---

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# bert_uncased_L-2_H-768_A-12_massive

This model is a fine-tuned version of [google/bert_uncased_L-2_H-768_A-12](https://huggingface.co/google/bert_uncased_L-2_H-768_A-12) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5434
- Accuracy: 0.8746

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5143        | 1.0   | 180  | 1.2564          | 0.7024   |
| 1.0135        | 2.0   | 360  | 0.7279          | 0.8205   |
| 0.6173        | 3.0   | 540  | 0.5817          | 0.8559   |
| 0.433         | 4.0   | 720  | 0.5234          | 0.8598   |
| 0.312         | 5.0   | 900  | 0.5019          | 0.8657   |
| 0.23          | 6.0   | 1080 | 0.5028          | 0.8711   |
| 0.1742        | 7.0   | 1260 | 0.5037          | 0.8682   |
| 0.1314        | 8.0   | 1440 | 0.5018          | 0.8692   |
| 0.1031        | 9.0   | 1620 | 0.5188          | 0.8731   |
| 0.081         | 10.0  | 1800 | 0.5231          | 0.8711   |
| 0.0671        | 11.0  | 1980 | 0.5407          | 0.8716   |
| 0.0569        | 12.0  | 2160 | 0.5309          | 0.8721   |
| 0.0466        | 13.0  | 2340 | 0.5463          | 0.8711   |
| 0.0414        | 14.0  | 2520 | 0.5434          | 0.8746   |
| 0.039         | 15.0  | 2700 | 0.5464          | 0.8721   |


### Framework versions

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