transformers pytorch bert text-classification generated_from_trainer dataset:massive base_model:google/bert_uncased_L-10_H-512_A-8 base_model:finetune:google/bert_uncased_L-10_H-512_A-8 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google/bert_uncased_L-10_H-512_A-8
datasets:
- massive
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert_uncased_L-10_H-512_A-8_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: 0.8868666994589277
      name: Accuracy
---

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# bert_uncased_L-10_H-512_A-8_massive

This model is a fine-tuned version of [google/bert_uncased_L-10_H-512_A-8](https://huggingface.co/google/bert_uncased_L-10_H-512_A-8) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6000
- Accuracy: 0.8869

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.4668        | 1.0   | 180  | 1.3269          | 0.7511   |
| 1.0706        | 2.0   | 360  | 0.7806          | 0.8411   |
| 0.6117        | 3.0   | 540  | 0.6024          | 0.8662   |
| 0.3953        | 4.0   | 720  | 0.5695          | 0.8692   |
| 0.2706        | 5.0   | 900  | 0.5476          | 0.8751   |
| 0.1872        | 6.0   | 1080 | 0.5291          | 0.8775   |
| 0.1345        | 7.0   | 1260 | 0.5455          | 0.8770   |
| 0.0982        | 8.0   | 1440 | 0.5429          | 0.8844   |
| 0.067         | 9.0   | 1620 | 0.5639          | 0.8854   |
| 0.0513        | 10.0  | 1800 | 0.5952          | 0.8775   |
| 0.0392        | 11.0  | 1980 | 0.5867          | 0.8834   |
| 0.0305        | 12.0  | 2160 | 0.6004          | 0.8785   |
| 0.0241        | 13.0  | 2340 | 0.5916          | 0.8849   |
| 0.0202        | 14.0  | 2520 | 0.6000          | 0.8869   |
| 0.0187        | 15.0  | 2700 | 0.6025          | 0.8859   |


### Framework versions

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