---
base_model: gokuls/HBERTv1_48_L10_H512_A8
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L10_H512_A8_massive
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: massive
      type: massive
      config: en-US
      split: validation
      args: en-US
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8583374323659616
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# HBERTv1_48_L10_H512_A8_massive

This model is a fine-tuned version of [gokuls/HBERTv1_48_L10_H512_A8](https://huggingface.co/gokuls/HBERTv1_48_L10_H512_A8) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8593
- Accuracy: 0.8583

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6536        | 1.0   | 180  | 1.3212          | 0.6542   |
| 1.0696        | 2.0   | 360  | 0.8384          | 0.7777   |
| 0.701         | 3.0   | 540  | 0.7514          | 0.8082   |
| 0.5181        | 4.0   | 720  | 0.7376          | 0.8096   |
| 0.3958        | 5.0   | 900  | 0.6764          | 0.8269   |
| 0.3031        | 6.0   | 1080 | 0.6955          | 0.8382   |
| 0.2378        | 7.0   | 1260 | 0.7173          | 0.8392   |
| 0.1719        | 8.0   | 1440 | 0.7289          | 0.8401   |
| 0.1294        | 9.0   | 1620 | 0.7609          | 0.8485   |
| 0.096         | 10.0  | 1800 | 0.7744          | 0.8465   |
| 0.0769        | 11.0  | 1980 | 0.8206          | 0.8490   |
| 0.05          | 12.0  | 2160 | 0.8085          | 0.8564   |
| 0.034         | 13.0  | 2340 | 0.8537          | 0.8534   |
| 0.0218        | 14.0  | 2520 | 0.8480          | 0.8564   |
| 0.0139        | 15.0  | 2700 | 0.8593          | 0.8583   |


### Framework versions

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