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_24_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: 0.7083333333333334
      name: Accuracy
    - type: f1
      value: 0.8199697428139183
      name: F1
---

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# sa_BERT_24_mrpc

This model is a fine-tuned version of [gokuls/bert_base_24](https://huggingface.co/gokuls/bert_base_24) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6042
- Accuracy: 0.7083
- F1: 0.8200
- Combined Score: 0.7642

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6437        | 1.0   | 39   | 0.6042          | 0.7083   | 0.8200 | 0.7642         |
| 0.5784        | 2.0   | 78   | 0.6224          | 0.6544   | 0.7403 | 0.6974         |
| 0.4657        | 3.0   | 117  | 0.7196          | 0.6740   | 0.7816 | 0.7278         |
| 0.3555        | 4.0   | 156  | 0.8929          | 0.6348   | 0.7418 | 0.6883         |
| 0.2516        | 5.0   | 195  | 1.0482          | 0.6078   | 0.6992 | 0.6535         |
| 0.1654        | 6.0   | 234  | 1.3865          | 0.5515   | 0.6131 | 0.5823         |


### Framework versions

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