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
tags:
- generated_from_trainer
model-index:
- name: sa_BERT_48_rte
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE RTE
      type: glue
      config: rte
      split: validation
      args: rte
    metrics:
    - type: accuracy
      value: 0.5306859205776173
      name: Accuracy
---

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# sa_BERT_48_rte

This model is a fine-tuned version of [gokuls/bert_base_48](https://huggingface.co/gokuls/bert_base_48) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6990
- Accuracy: 0.5307

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7322        | 1.0   | 26   | 0.7111          | 0.4729   |
| 0.7015        | 2.0   | 52   | 0.6990          | 0.5307   |
| 0.6641        | 3.0   | 78   | 0.7983          | 0.5090   |
| 0.4974        | 4.0   | 104  | 1.1008          | 0.5271   |
| 0.3758        | 5.0   | 130  | 1.2088          | 0.4801   |
| 0.2588        | 6.0   | 156  | 1.4545          | 0.5162   |
| 0.1716        | 7.0   | 182  | 1.4467          | 0.5090   |


### Framework versions

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