---
base_model: gokuls/HBERTv1_48_L4_H64_A2
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L4_H64_A2_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: 0.32611903590752583
---

<!-- 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_L4_H64_A2_massive

This model is a fine-tuned version of [gokuls/HBERTv1_48_L4_H64_A2](https://huggingface.co/gokuls/HBERTv1_48_L4_H64_A2) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3014
- Accuracy: 0.3261

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.0           | 1.0   | 180  | 3.8278          | 0.0723   |
| 3.6366        | 2.0   | 360  | 3.4279          | 0.1117   |
| 3.3385        | 3.0   | 540  | 3.1935          | 0.1638   |
| 3.1113        | 4.0   | 720  | 2.9828          | 0.1909   |
| 2.9324        | 5.0   | 900  | 2.8344          | 0.2130   |
| 2.7882        | 6.0   | 1080 | 2.7100          | 0.2523   |
| 2.6832        | 7.0   | 1260 | 2.6215          | 0.2774   |
| 2.5965        | 8.0   | 1440 | 2.5459          | 0.2887   |
| 2.5244        | 9.0   | 1620 | 2.4872          | 0.2966   |
| 2.4603        | 10.0  | 1800 | 2.4261          | 0.3010   |
| 2.3987        | 11.0  | 1980 | 2.3758          | 0.3153   |
| 2.3615        | 12.0  | 2160 | 2.3469          | 0.3217   |
| 2.3292        | 13.0  | 2340 | 2.3241          | 0.3212   |
| 2.3071        | 14.0  | 2520 | 2.3100          | 0.3212   |
| 2.288         | 15.0  | 2700 | 2.3014          | 0.3261   |


### Framework versions

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