transformers pytorch tensorboard bert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: sa_BERT_48_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: 0.6519607843137255
      name: Accuracy
    - type: f1
      value: 0.726923076923077
      name: F1
---

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# sa_BERT_48_mrpc

This model is a fine-tuned version of [gokuls/bert_base_48](https://huggingface.co/gokuls/bert_base_48) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6401
- Accuracy: 0.6520
- F1: 0.7269
- Combined Score: 0.6894

## 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: 96
- eval_batch_size: 96
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6588        | 1.0   | 39   | 0.6401          | 0.6520   | 0.7269 | 0.6894         |
| 0.5982        | 2.0   | 78   | 0.6441          | 0.6863   | 0.7801 | 0.7332         |
| 0.4614        | 3.0   | 117  | 0.6615          | 0.6740   | 0.7787 | 0.7264         |
| 0.3148        | 4.0   | 156  | 0.7447          | 0.6765   | 0.7770 | 0.7267         |
| 0.226         | 5.0   | 195  | 0.9718          | 0.6054   | 0.6957 | 0.6505         |
| 0.1566        | 6.0   | 234  | 1.2879          | 0.5564   | 0.6268 | 0.5916         |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
