---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: olm-bert-tiny-december-2022-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. -->

# olm-bert-tiny-december-2022-target-glue-qnli

This model is a fine-tuned version of [muhtasham/olm-bert-tiny-december-2022](https://huggingface.co/muhtasham/olm-bert-tiny-december-2022) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6358
- Accuracy: 0.6306

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.692         | 0.15  | 500  | 0.6882          | 0.5574   |
| 0.6777        | 0.31  | 1000 | 0.6637          | 0.6059   |
| 0.667         | 0.46  | 1500 | 0.6568          | 0.6064   |
| 0.6609        | 0.61  | 2000 | 0.6517          | 0.6193   |
| 0.6596        | 0.76  | 2500 | 0.6514          | 0.6127   |
| 0.6584        | 0.92  | 3000 | 0.6496          | 0.6202   |
| 0.6514        | 1.07  | 3500 | 0.6487          | 0.6191   |
| 0.652         | 1.22  | 4000 | 0.6420          | 0.6253   |
| 0.6449        | 1.37  | 4500 | 0.6415          | 0.6268   |
| 0.6477        | 1.53  | 5000 | 0.6358          | 0.6306   |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2