transformers pytorch tensorboard bert text-classification generated_from_trainer dataset:massive license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- massive
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert-base-Massive-intent_48
  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: 0.8622725036891293
      name: Accuracy
---

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# bert-base-Massive-intent_48

This model is a fine-tuned version of [gokuls/bert_base_48](https://huggingface.co/gokuls/bert_base_48) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6203
- Accuracy: 0.8623

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6304        | 1.0   | 180  | 0.8747          | 0.7821   |
| 0.6654        | 2.0   | 360  | 0.6418          | 0.8347   |
| 0.4063        | 3.0   | 540  | 0.5890          | 0.8529   |
| 0.2592        | 4.0   | 720  | 0.6132          | 0.8446   |
| 0.1832        | 5.0   | 900  | 0.6417          | 0.8519   |
| 0.1357        | 6.0   | 1080 | 0.6203          | 0.8623   |
| 0.0969        | 7.0   | 1260 | 0.6742          | 0.8534   |
| 0.0735        | 8.0   | 1440 | 0.7212          | 0.8436   |
| 0.0532        | 9.0   | 1620 | 0.7192          | 0.8529   |
| 0.0378        | 10.0  | 1800 | 0.7625          | 0.8564   |
| 0.0298        | 11.0  | 1980 | 0.7275          | 0.8588   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
