transformers pytorch hybridbert text-classification generated_from_trainer en dataset:glue base_model:gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48 base_model:finetune:gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48
datasets:
- glue
language:
- en
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: hBERTv2_new_pretrain_w_init_48_ver2_mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.6813725490196079
      name: Accuracy
    - type: f1
      value: 0.7875816993464053
      name: F1
---

<!-- 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. -->

# hBERTv2_new_pretrain_w_init_48_ver2_mrpc

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6098
- Accuracy: 0.6814
- F1: 0.7876
- Combined Score: 0.7345

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6536        | 1.0   | 58   | 0.6201          | 0.6667   | 0.7785 | 0.7226         |
| 0.6165        | 2.0   | 116  | 0.6098          | 0.6814   | 0.7876 | 0.7345         |
| 0.5699        | 3.0   | 174  | 0.6265          | 0.6593   | 0.7352 | 0.6973         |
| 0.4763        | 4.0   | 232  | 0.6630          | 0.6887   | 0.7873 | 0.7380         |
| 0.3676        | 5.0   | 290  | 0.8272          | 0.7083   | 0.8114 | 0.7599         |
| 0.2392        | 6.0   | 348  | 1.0790          | 0.6495   | 0.7597 | 0.7046         |
| 0.1663        | 7.0   | 406  | 1.5179          | 0.6225   | 0.7169 | 0.6697         |


### Framework versions

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