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ghazikhanihamed
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TooT-PLM-P2S

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
Model card Files Community
ghazikhanihamed commited on
Commit
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1 Parent(s): 53ee41e

PLM-Secondary-Structure-Generation

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Files changed (4) hide show
  1. README.md +17 -12
  2. pytorch_model.bin +1 -1
  3. tokenizer.json +2 -2
  4. training_args.bin +1 -1
README.md CHANGED
@@ -15,8 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ElnaggarLab/ankh-base](https://huggingface.co/ElnaggarLab/ankh-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2293
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- - Q3 Accuracy: 0.6740
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  ## Model description
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@@ -36,28 +36,33 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.001
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- - train_batch_size: 2
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- - eval_batch_size: 2
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  - seed: 7
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  - distributed_type: multi-GPU
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  - num_devices: 4
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- - gradient_accumulation_steps: 2
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  - total_train_batch_size: 16
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- - total_eval_batch_size: 8
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 1000
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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Q3 Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------:|
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- | 0.2825 | 1.0 | 706 | 0.2635 | 0.6740 |
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- | 0.4734 | 2.0 | 1413 | 0.2550 | 0.6740 |
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- | 0.2398 | 3.0 | 2119 | 0.2318 | 0.6740 |
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- | 0.2392 | 4.0 | 2826 | 0.2324 | 0.6740 |
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- | 0.2363 | 5.0 | 3530 | 0.2293 | 0.6740 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [ElnaggarLab/ankh-base](https://huggingface.co/ElnaggarLab/ankh-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1438
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+ - Q3 Accuracy: 0.7841
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.001
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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  - seed: 7
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  - distributed_type: multi-GPU
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  - num_devices: 4
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+ - gradient_accumulation_steps: 4
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  - total_train_batch_size: 16
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+ - total_eval_batch_size: 4
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 1000
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Q3 Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------:|
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+ | 0.1995 | 1.0 | 706 | 0.1747 | 0.7530 |
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+ | 0.1722 | 2.0 | 1413 | 0.1628 | 0.7530 |
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+ | 0.1657 | 3.0 | 2119 | 0.1604 | 0.7530 |
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+ | 0.164 | 4.0 | 2826 | 0.1567 | 0.7534 |
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+ | 0.1612 | 5.0 | 3532 | 0.1538 | 0.7518 |
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+ | 0.1554 | 6.0 | 4239 | 0.1513 | 0.7670 |
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+ | 0.154 | 7.0 | 4945 | 0.1500 | 0.7391 |
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+ | 0.1508 | 8.0 | 5652 | 0.1468 | 0.7778 |
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+ | 0.1502 | 9.0 | 6358 | 0.1453 | 0.8144 |
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+ | 0.1437 | 9.99 | 7060 | 0.1438 | 0.7841 |
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  ### Framework versions
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