update model card README.md

README.md

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+---
+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