transformers tensorboard safetensors hybridbert text-classification generated_from_trainer dataset:massive base_model:gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_2 base_model:finetune:gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_2 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_2
datasets:
- massive
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hbertv1-massive-logit_KD-tiny_ffn_2
  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: 0.8312838170191835
      name: Accuracy
---

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# hbertv1-massive-logit_KD-tiny_ffn_2

This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_2](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_2) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6148
- Accuracy: 0.8313

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.1929        | 1.0   | 180  | 3.5935          | 0.1402   |
| 3.4611        | 2.0   | 360  | 3.0049          | 0.2941   |
| 2.9024        | 3.0   | 540  | 2.4730          | 0.3792   |
| 2.4356        | 4.0   | 720  | 2.0721          | 0.4515   |
| 2.1041        | 5.0   | 900  | 1.8179          | 0.5278   |
| 1.8564        | 6.0   | 1080 | 1.6004          | 0.6257   |
| 1.6676        | 7.0   | 1260 | 1.4500          | 0.6596   |
| 1.5135        | 8.0   | 1440 | 1.3147          | 0.6995   |
| 1.3906        | 9.0   | 1620 | 1.2211          | 0.7147   |
| 1.2811        | 10.0  | 1800 | 1.1393          | 0.7314   |
| 1.1937        | 11.0  | 1980 | 1.0803          | 0.7304   |
| 1.112         | 12.0  | 2160 | 1.0267          | 0.7467   |
| 1.0488        | 13.0  | 2340 | 0.9716          | 0.7570   |
| 0.983         | 14.0  | 2520 | 0.9306          | 0.7649   |
| 0.9294        | 15.0  | 2700 | 0.8892          | 0.7767   |
| 0.8909        | 16.0  | 2880 | 0.8578          | 0.7885   |
| 0.8436        | 17.0  | 3060 | 0.8270          | 0.7909   |
| 0.8078        | 18.0  | 3240 | 0.8201          | 0.7964   |
| 0.7777        | 19.0  | 3420 | 0.7934          | 0.8028   |
| 0.7433        | 20.0  | 3600 | 0.7792          | 0.8037   |
| 0.7121        | 21.0  | 3780 | 0.7504          | 0.8082   |
| 0.6896        | 22.0  | 3960 | 0.7433          | 0.8091   |
| 0.6592        | 23.0  | 4140 | 0.7200          | 0.8160   |
| 0.6389        | 24.0  | 4320 | 0.7177          | 0.8096   |
| 0.6175        | 25.0  | 4500 | 0.7039          | 0.8136   |
| 0.6024        | 26.0  | 4680 | 0.6928          | 0.8180   |
| 0.5835        | 27.0  | 4860 | 0.6940          | 0.8170   |
| 0.5673        | 28.0  | 5040 | 0.6787          | 0.8136   |
| 0.5523        | 29.0  | 5220 | 0.6680          | 0.8229   |
| 0.5445        | 30.0  | 5400 | 0.6599          | 0.8234   |
| 0.5319        | 31.0  | 5580 | 0.6634          | 0.8214   |
| 0.5196        | 32.0  | 5760 | 0.6549          | 0.8259   |
| 0.504         | 33.0  | 5940 | 0.6506          | 0.8239   |
| 0.4993        | 34.0  | 6120 | 0.6518          | 0.8249   |
| 0.4941        | 35.0  | 6300 | 0.6388          | 0.8239   |
| 0.4823        | 36.0  | 6480 | 0.6317          | 0.8278   |
| 0.4734        | 37.0  | 6660 | 0.6327          | 0.8288   |
| 0.4609        | 38.0  | 6840 | 0.6312          | 0.8239   |
| 0.4617        | 39.0  | 7020 | 0.6279          | 0.8288   |
| 0.4529        | 40.0  | 7200 | 0.6255          | 0.8273   |
| 0.4491        | 41.0  | 7380 | 0.6173          | 0.8288   |
| 0.4419        | 42.0  | 7560 | 0.6148          | 0.8313   |
| 0.4378        | 43.0  | 7740 | 0.6208          | 0.8298   |
| 0.4362        | 44.0  | 7920 | 0.6140          | 0.8288   |
| 0.432         | 45.0  | 8100 | 0.6152          | 0.8308   |
| 0.4276        | 46.0  | 8280 | 0.6150          | 0.8288   |
| 0.4263        | 47.0  | 8460 | 0.6118          | 0.8308   |


### Framework versions

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