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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: muhtasham/olm-bert-tiny-december-2022
model-index:
- name: olm-bert-tiny-december-2022-target-glue-rte
  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-rte

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: 1.3103
- Accuracy: 0.5235

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6883        | 6.41  | 500  | 0.6919          | 0.5523   |
| 0.5979        | 12.82 | 1000 | 0.8002          | 0.5271   |
| 0.4213        | 19.23 | 1500 | 1.0720          | 0.5090   |
| 0.2839        | 25.64 | 2000 | 1.3103          | 0.5235   |


### Framework versions

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