---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: small-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. -->

# small-vanilla-target-glue-qnli

This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3458
- Accuracy: 0.8583

## 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
- training_steps: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.488         | 0.15  | 500  | 0.3901          | 0.8316   |
| 0.4449        | 0.31  | 1000 | 0.3826          | 0.8373   |
| 0.4243        | 0.46  | 1500 | 0.3596          | 0.8448   |
| 0.4133        | 0.61  | 2000 | 0.3663          | 0.8417   |
| 0.4102        | 0.76  | 2500 | 0.3459          | 0.8499   |
| 0.3924        | 0.92  | 3000 | 0.3286          | 0.8585   |
| 0.3539        | 1.07  | 3500 | 0.3467          | 0.8532   |
| 0.3202        | 1.22  | 4000 | 0.3478          | 0.8636   |
| 0.3183        | 1.37  | 4500 | 0.3574          | 0.8514   |
| 0.3215        | 1.53  | 5000 | 0.3458          | 0.8583   |


### Framework versions

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