metadata
license: cc-by-nc-sa-4.0
base_model: ElnaggarLab/ankh-base
tags:
- generated_from_trainer
model-index:
- name: TooT-PLM-P2S
results: []
TooT-PLM-P2S
This model is a fine-tuned version of ElnaggarLab/ankh-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1575
- Q3 Accuracy: 0.5314
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: 1
- eval_batch_size: 1
- seed: 7
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Q3 Accuracy |
|---|---|---|---|---|
| 0.6057 | 1.0 | 318 | 0.2338 | 0.4211 |
| 0.214 | 2.0 | 636 | 0.1712 | 0.6755 |
| 0.2068 | 3.0 | 954 | 0.1697 | 0.6628 |
| 0.2178 | 4.0 | 1272 | 0.1755 | 0.3646 |
| 0.1815 | 5.0 | 1590 | 0.1678 | 0.6628 |
| 0.1768 | 6.0 | 1908 | 0.1667 | 0.6628 |
| 0.1682 | 7.0 | 2226 | 0.1650 | 0.6628 |
| 0.1626 | 8.0 | 2544 | 0.1693 | 0.6527 |
| 0.1609 | 9.0 | 2862 | 0.1594 | 0.6566 |
| 0.1577 | 10.0 | 3180 | 0.1575 | 0.5314 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.5
- Tokenizers 0.14.1