---
language:
- en
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv1_new_pretrain_w_init_48_ver2_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7181372549019608
    - name: F1
      type: f1
      value: 0.8099173553719009
---

<!-- 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_mrpc

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 MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5916
- Accuracy: 0.7181
- F1: 0.8099
- Combined Score: 0.7640

## 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 | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6666        | 1.0   | 58   | 0.6274          | 0.6912   | 0.8006 | 0.7459         |
| 0.6239        | 2.0   | 116  | 0.5916          | 0.7181   | 0.8099 | 0.7640         |
| 0.5981        | 3.0   | 174  | 0.6532          | 0.6225   | 0.7004 | 0.6615         |
| 0.518         | 4.0   | 232  | 0.6251          | 0.7108   | 0.8059 | 0.7584         |
| 0.3848        | 5.0   | 290  | 0.7553          | 0.6814   | 0.7869 | 0.7341         |
| 0.2708        | 6.0   | 348  | 1.0696          | 0.6838   | 0.7994 | 0.7416         |
| 0.2062        | 7.0   | 406  | 1.2159          | 0.6103   | 0.7145 | 0.6624         |


### Framework versions

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