---
language:
- en
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv1_new_pretrain_w_init_48_ver2_sst2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE SST2
      type: glue
      config: sst2
      split: validation
      args: sst2
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5091743119266054
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hBERTv1_new_pretrain_w_init_48_ver2_sst2

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6941
- Accuracy: 0.5092

## 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: 64
- eval_batch_size: 64
- seed: 10
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6948        | 1.0   | 1053 | 0.6948          | 0.5092   |
| 0.6927        | 2.0   | 2106 | 0.6941          | 0.5092   |
| 0.6879        | 3.0   | 3159 | 0.7005          | 0.5092   |
| 0.6873        | 4.0   | 4212 | 0.7004          | 0.5092   |
| 0.6887        | 5.0   | 5265 | 0.7151          | 0.5092   |
| 0.6871        | 6.0   | 6318 | 0.6975          | 0.5092   |
| 0.6859        | 7.0   | 7371 | 0.7068          | 0.5092   |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1