transformers pytorch tensorboard hybridbert text-classification generated_from_trainer en dataset:glue model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hBERTv1_new_pretrain_48_emb_com_sst2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE SST2
      type: glue
      config: sst2
      split: validation
      args: sst2
    metrics:
    - type: accuracy
      value: 0.7947247706422018
      name: Accuracy
---

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# hBERTv1_new_pretrain_48_emb_com_sst2

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48) on the GLUE SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4656
- Accuracy: 0.7947

## 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: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 10
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4711        | 1.0   | 527  | 0.4730          | 0.7787   |
| 0.2942        | 2.0   | 1054 | 0.5417          | 0.7993   |
| 0.228         | 3.0   | 1581 | 0.5140          | 0.7901   |
| 0.1897        | 4.0   | 2108 | 0.4951          | 0.7947   |
| 0.1608        | 5.0   | 2635 | 0.4656          | 0.7947   |
| 0.1422        | 6.0   | 3162 | 0.6786          | 0.7741   |
| 0.1244        | 7.0   | 3689 | 0.6886          | 0.8028   |
| 0.1112        | 8.0   | 4216 | 0.7387          | 0.7821   |
| 0.0985        | 9.0   | 4743 | 0.7169          | 0.7936   |
| 0.0883        | 10.0  | 5270 | 0.7695          | 0.7959   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
