transformers pytorch hybridbert text-classification generated_from_trainer dataset:massive base_model:gokuls/HBERTv1_48_L8_H64_A2 base_model:finetune:gokuls/HBERTv1_48_L8_H64_A2 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/HBERTv1_48_L8_H64_A2
datasets:
- massive
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: HBERTv1_48_L8_H64_A2_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: 0.45056566650270535
      name: Accuracy
---

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# HBERTv1_48_L8_H64_A2_massive

This model is a fine-tuned version of [gokuls/HBERTv1_48_L8_H64_A2](https://huggingface.co/gokuls/HBERTv1_48_L8_H64_A2) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0023
- Accuracy: 0.4506

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9694        | 1.0   | 180  | 3.7614          | 0.0949   |
| 3.5709        | 2.0   | 360  | 3.3717          | 0.1323   |
| 3.2745        | 3.0   | 540  | 3.1313          | 0.1968   |
| 3.0491        | 4.0   | 720  | 2.9227          | 0.2086   |
| 2.8486        | 5.0   | 900  | 2.7431          | 0.2238   |
| 2.6671        | 6.0   | 1080 | 2.5865          | 0.2848   |
| 2.514         | 7.0   | 1260 | 2.4468          | 0.3212   |
| 2.3707        | 8.0   | 1440 | 2.3252          | 0.3620   |
| 2.262         | 9.0   | 1620 | 2.2383          | 0.3866   |
| 2.1746        | 10.0  | 1800 | 2.1570          | 0.4171   |
| 2.0999        | 11.0  | 1980 | 2.1083          | 0.4309   |
| 2.0442        | 12.0  | 2160 | 2.0581          | 0.4383   |
| 1.9992        | 13.0  | 2340 | 2.0297          | 0.4432   |
| 1.9728        | 14.0  | 2520 | 2.0104          | 0.4461   |
| 1.9461        | 15.0  | 2700 | 2.0023          | 0.4506   |


### Framework versions

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