---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: add_BERT_no_pretrain_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: 0.696078431372549
    - name: F1
      type: f1
      value: 0.7933333333333332
---

<!-- 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. -->

# add_BERT_no_pretrain_mrpc

This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5912
- Accuracy: 0.6961
- F1: 0.7933
- Combined Score: 0.7447

## 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 | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6854        | 1.0   | 29   | 0.6711          | 0.6838   | 0.8122 | 0.7480         |
| 0.6496        | 2.0   | 58   | 0.6802          | 0.6838   | 0.8122 | 0.7480         |
| 0.648         | 3.0   | 87   | 0.6246          | 0.6838   | 0.8122 | 0.7480         |
| 0.6363        | 4.0   | 116  | 0.6174          | 0.6838   | 0.8122 | 0.7480         |
| 0.6049        | 5.0   | 145  | 0.6176          | 0.6593   | 0.7459 | 0.7026         |
| 0.5491        | 6.0   | 174  | 0.6038          | 0.6814   | 0.7950 | 0.7382         |
| 0.5601        | 7.0   | 203  | 0.5912          | 0.6961   | 0.7933 | 0.7447         |
| 0.5505        | 8.0   | 232  | 0.6346          | 0.6716   | 0.7781 | 0.7249         |
| 0.5327        | 9.0   | 261  | 0.6283          | 0.6544   | 0.7531 | 0.7037         |
| 0.529         | 10.0  | 290  | 0.6341          | 0.6520   | 0.7568 | 0.7044         |
| 0.5337        | 11.0  | 319  | 0.6285          | 0.6618   | 0.7579 | 0.7098         |
| 0.5383        | 12.0  | 348  | 0.6322          | 0.6348   | 0.7286 | 0.6817         |


### Framework versions

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