---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tiny-vanilla-target-glue-qnli
  results: []
---

<!-- 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. -->

# tiny-vanilla-target-glue-qnli

This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4624
- Accuracy: 0.7825

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6082        | 0.15  | 500  | 0.5375          | 0.7362   |
| 0.5378        | 0.31  | 1000 | 0.5192          | 0.7459   |
| 0.5161        | 0.46  | 1500 | 0.4967          | 0.7672   |
| 0.5097        | 0.61  | 2000 | 0.5182          | 0.7505   |
| 0.5092        | 0.76  | 2500 | 0.4728          | 0.7750   |
| 0.5011        | 0.92  | 3000 | 0.4660          | 0.7866   |
| 0.4889        | 1.07  | 3500 | 0.4476          | 0.7922   |
| 0.48          | 1.22  | 4000 | 0.4619          | 0.7840   |
| 0.4661        | 1.37  | 4500 | 0.4813          | 0.7741   |
| 0.4742        | 1.53  | 5000 | 0.4624          | 0.7825   |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2