transformers tensorboard safetensors hybridbert text-classification generated_from_trainer dataset:massive base_model:gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new base_model:finetune:gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new
datasets:
- massive
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hbertv1-massive-logit_KD-tiny
  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: 0.8465322183964584
      name: Accuracy
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hbertv1-massive-logit_KD-tiny

This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5468
- Accuracy: 0.8465

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.0471        | 1.0   | 180  | 3.2580          | 0.2258   |
| 2.9727        | 2.0   | 360  | 2.3478          | 0.3778   |
| 2.3183        | 3.0   | 540  | 1.8643          | 0.5081   |
| 1.9162        | 4.0   | 720  | 1.5331          | 0.6375   |
| 1.6284        | 5.0   | 900  | 1.3079          | 0.6931   |
| 1.4163        | 6.0   | 1080 | 1.1495          | 0.7241   |
| 1.263         | 7.0   | 1260 | 1.0287          | 0.7437   |
| 1.1491        | 8.0   | 1440 | 0.9566          | 0.7575   |
| 1.0652        | 9.0   | 1620 | 0.8881          | 0.7644   |
| 0.9661        | 10.0  | 1800 | 0.8426          | 0.7801   |
| 0.9077        | 11.0  | 1980 | 0.7980          | 0.7796   |
| 0.8466        | 12.0  | 2160 | 0.7675          | 0.7919   |
| 0.7996        | 13.0  | 2340 | 0.7422          | 0.7934   |
| 0.7605        | 14.0  | 2520 | 0.7323          | 0.7954   |
| 0.7156        | 15.0  | 2700 | 0.6864          | 0.8067   |
| 0.6867        | 16.0  | 2880 | 0.6730          | 0.8131   |
| 0.6493        | 17.0  | 3060 | 0.6548          | 0.8160   |
| 0.6245        | 18.0  | 3240 | 0.6495          | 0.8136   |
| 0.6038        | 19.0  | 3420 | 0.6282          | 0.8224   |
| 0.57          | 20.0  | 3600 | 0.6123          | 0.8224   |
| 0.556         | 21.0  | 3780 | 0.6020          | 0.8308   |
| 0.5334        | 22.0  | 3960 | 0.5943          | 0.8298   |
| 0.5101        | 23.0  | 4140 | 0.5778          | 0.8323   |
| 0.4948        | 24.0  | 4320 | 0.5740          | 0.8337   |
| 0.4824        | 25.0  | 4500 | 0.5772          | 0.8337   |
| 0.4728        | 26.0  | 4680 | 0.5712          | 0.8342   |
| 0.4596        | 27.0  | 4860 | 0.5691          | 0.8337   |
| 0.4436        | 28.0  | 5040 | 0.5670          | 0.8396   |
| 0.4367        | 29.0  | 5220 | 0.5542          | 0.8367   |
| 0.4249        | 30.0  | 5400 | 0.5512          | 0.8406   |
| 0.4117        | 31.0  | 5580 | 0.5450          | 0.8387   |
| 0.4051        | 32.0  | 5760 | 0.5468          | 0.8465   |
| 0.4           | 33.0  | 5940 | 0.5464          | 0.8401   |
| 0.3939        | 34.0  | 6120 | 0.5451          | 0.8446   |
| 0.3801        | 35.0  | 6300 | 0.5387          | 0.8441   |
| 0.3708        | 36.0  | 6480 | 0.5353          | 0.8421   |
| 0.3686        | 37.0  | 6660 | 0.5320          | 0.8455   |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.15.0
- Tokenizers 0.15.0
