transformers pytorch hybridbert text-classification generated_from_trainer dataset:massive base_model:gokuls/HBERTv1_48_L10_H128_A2 base_model:finetune:gokuls/HBERTv1_48_L10_H128_A2 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/HBERTv1_48_L10_H128_A2
datasets:
- massive
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: HBERTv1_48_L10_H128_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: 0.7550418101328087
      name: Accuracy
---

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# HBERTv1_48_L10_H128_A2_massive

This model is a fine-tuned version of [gokuls/HBERTv1_48_L10_H128_A2](https://huggingface.co/gokuls/HBERTv1_48_L10_H128_A2) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0992
- Accuracy: 0.7550

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.7898        | 1.0   | 180  | 3.3951          | 0.2120   |
| 3.0906        | 2.0   | 360  | 2.7701          | 0.3261   |
| 2.5803        | 3.0   | 540  | 2.3090          | 0.4235   |
| 2.1582        | 4.0   | 720  | 1.9427          | 0.5027   |
| 1.824         | 5.0   | 900  | 1.6937          | 0.5898   |
| 1.5669        | 6.0   | 1080 | 1.5220          | 0.6296   |
| 1.3731        | 7.0   | 1260 | 1.3841          | 0.6690   |
| 1.2237        | 8.0   | 1440 | 1.2811          | 0.6965   |
| 1.1037        | 9.0   | 1620 | 1.2167          | 0.7127   |
| 1.0132        | 10.0  | 1800 | 1.1843          | 0.7177   |
| 0.9387        | 11.0  | 1980 | 1.1377          | 0.7275   |
| 0.8742        | 12.0  | 2160 | 1.1167          | 0.7437   |
| 0.8335        | 13.0  | 2340 | 1.1076          | 0.7486   |
| 0.7923        | 14.0  | 2520 | 1.0992          | 0.7550   |
| 0.7673        | 15.0  | 2700 | 1.0983          | 0.7516   |


### Framework versions

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