---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: olm-bert-tiny-december-2022-target-glue-sst2
  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-sst2

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: 0.4126
- Accuracy: 0.8280

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5968        | 0.24  | 500  | 0.4910          | 0.7718   |
| 0.4845        | 0.48  | 1000 | 0.4722          | 0.7810   |
| 0.4455        | 0.71  | 1500 | 0.4468          | 0.7924   |
| 0.4397        | 0.95  | 2000 | 0.4488          | 0.7901   |
| 0.4028        | 1.19  | 2500 | 0.4262          | 0.8119   |
| 0.3898        | 1.43  | 3000 | 0.4375          | 0.7936   |
| 0.3768        | 1.66  | 3500 | 0.4207          | 0.8050   |
| 0.3725        | 1.9   | 4000 | 0.4228          | 0.8245   |
| 0.3515        | 2.14  | 4500 | 0.4336          | 0.8085   |
| 0.3326        | 2.38  | 5000 | 0.4126          | 0.8280   |


### Framework versions

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