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

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: 2.4058
- Pearson: 0.3207
- Spearmanr: 0.3227

## 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 | Pearson | Spearmanr |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
| 3.7225        | 2.78  | 500  | 2.3571          | 0.0394  | 0.0504    |
| 1.9638        | 5.56  | 1000 | 2.3486          | 0.1721  | 0.1893    |
| 1.7812        | 8.33  | 1500 | 2.3649          | 0.2248  | 0.2401    |
| 1.5724        | 11.11 | 2000 | 2.3334          | 0.2645  | 0.2767    |
| 1.3776        | 13.89 | 2500 | 2.4034          | 0.2785  | 0.2861    |
| 1.2174        | 16.67 | 3000 | 2.3773          | 0.2963  | 0.3043    |
| 1.0875        | 19.44 | 3500 | 2.3327          | 0.3213  | 0.3205    |
| 0.9406        | 22.22 | 4000 | 2.3715          | 0.3216  | 0.3222    |
| 0.8757        | 25.0  | 4500 | 2.3264          | 0.3274  | 0.3281    |
| 0.7946        | 27.78 | 5000 | 2.4058          | 0.3207  | 0.3227    |


### Framework versions

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