transformers pytorch bert text-classification generated_from_trainer dataset:massive base_model:google/bert_uncased_L-12_H-256_A-4 base_model:finetune:google/bert_uncased_L-12_H-256_A-4 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google/bert_uncased_L-12_H-256_A-4
datasets:
- massive
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert_uncased_L-12_H-256_A-4_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: 0.8617806197737334
      name: Accuracy
---

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# bert_uncased_L-12_H-256_A-4_massive

This model is a fine-tuned version of [google/bert_uncased_L-12_H-256_A-4](https://huggingface.co/google/bert_uncased_L-12_H-256_A-4) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6679
- Accuracy: 0.8618

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.3504        | 1.0   | 180  | 2.5753          | 0.5726   |
| 2.2201        | 2.0   | 360  | 1.7801          | 0.7280   |
| 1.5878        | 3.0   | 540  | 1.3596          | 0.7747   |
| 1.218         | 4.0   | 720  | 1.1112          | 0.8032   |
| 0.9707        | 5.0   | 900  | 0.9673          | 0.8111   |
| 0.7935        | 6.0   | 1080 | 0.8617          | 0.8313   |
| 0.6704        | 7.0   | 1260 | 0.8082          | 0.8455   |
| 0.572         | 8.0   | 1440 | 0.7746          | 0.8446   |
| 0.5015        | 9.0   | 1620 | 0.7387          | 0.8500   |
| 0.4434        | 10.0  | 1800 | 0.7024          | 0.8534   |
| 0.3947        | 11.0  | 1980 | 0.7013          | 0.8549   |
| 0.362         | 12.0  | 2160 | 0.6884          | 0.8544   |
| 0.3365        | 13.0  | 2340 | 0.6821          | 0.8549   |
| 0.3172        | 14.0  | 2520 | 0.6704          | 0.8593   |
| 0.3067        | 15.0  | 2700 | 0.6679          | 0.8618   |


### Framework versions

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