---
license: cc-by-nc-sa-4.0
base_model: ElnaggarLab/ankh-base
tags:
- generated_from_trainer
model-index:
- name: TooT-PLM-P2S
  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. -->

# TooT-PLM-P2S

This model is a fine-tuned version of [ElnaggarLab/ankh-base](https://huggingface.co/ElnaggarLab/ankh-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2604
- Q3 Accuracy: 0.5425

## 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: 0.001
- train_batch_size: 2
- eval_batch_size: 16
- seed: 7
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 8
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Q3 Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.5495        | 0.35  | 500  | 0.2746          | 0.5425      |
| 0.2733        | 0.71  | 1000 | 0.2604          | 0.5425      |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.2