transformers pytorch hybridbert text-classification generated_from_trainer dataset:massive base_model:gokuls/HBERTv1_48_L12_H256_A4 base_model:finetune:gokuls/HBERTv1_48_L12_H256_A4 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/HBERTv1_48_L12_H256_A4
datasets:
- massive
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: HBERTv1_48_L12_H256_A4_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: 0.7338908017707821
      name: Accuracy
---

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# HBERTv1_48_L12_H256_A4_massive

This model is a fine-tuned version of [gokuls/HBERTv1_48_L12_H256_A4](https://huggingface.co/gokuls/HBERTv1_48_L12_H256_A4) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1699
- Accuracy: 0.7339

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.7238        | 1.0   | 180  | 3.4052          | 0.1382   |
| 3.1325        | 2.0   | 360  | 2.8875          | 0.2022   |
| 2.7162        | 3.0   | 540  | 2.5311          | 0.3030   |
| 2.4123        | 4.0   | 720  | 2.3315          | 0.3576   |
| 2.1258        | 5.0   | 900  | 2.0547          | 0.4186   |
| 1.8697        | 6.0   | 1080 | 1.8215          | 0.4889   |
| 1.6446        | 7.0   | 1260 | 1.6681          | 0.5421   |
| 1.4509        | 8.0   | 1440 | 1.5200          | 0.5853   |
| 1.2995        | 9.0   | 1620 | 1.4177          | 0.6188   |
| 1.1585        | 10.0  | 1800 | 1.3337          | 0.6557   |
| 1.0714        | 11.0  | 1980 | 1.2620          | 0.7059   |
| 0.9816        | 12.0  | 2160 | 1.2374          | 0.7147   |
| 0.9053        | 13.0  | 2340 | 1.1849          | 0.7290   |
| 0.8582        | 14.0  | 2520 | 1.1721          | 0.7324   |
| 0.8253        | 15.0  | 2700 | 1.1699          | 0.7339   |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
