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--- |
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license: cc-by-nc-sa-4.0 |
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base_model: InstaDeepAI/nucleotide-transformer-500m-human-ref |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: gut_1024-finetuned-lora-NT-500m-human-ref |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# gut_1024-finetuned-lora-NT-500m-human-ref |
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This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-500m-human-ref](https://huggingface.co/InstaDeepAI/nucleotide-transformer-500m-human-ref) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5875 |
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- F1: 0.7769 |
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- Mcc Score: 0.3628 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0005 |
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- train_batch_size: 8 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Mcc Score | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:| |
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| 0.8285 | 0.02 | 100 | 0.6805 | 0.7478 | 0.0 | |
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| 0.7353 | 0.04 | 200 | 0.6825 | 0.7478 | 0.0 | |
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| 0.7131 | 0.05 | 300 | 0.6285 | 0.7644 | 0.2641 | |
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| 0.7292 | 0.07 | 400 | 0.6473 | 0.7680 | 0.3281 | |
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| 0.6666 | 0.09 | 500 | 0.6445 | 0.7199 | 0.3140 | |
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| 0.6413 | 0.11 | 600 | 0.6176 | 0.7702 | 0.3201 | |
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| 0.6056 | 0.12 | 700 | 0.6388 | 0.7170 | 0.3337 | |
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| 0.6215 | 0.14 | 800 | 0.6161 | 0.7506 | 0.3337 | |
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| 0.596 | 0.16 | 900 | 0.6000 | 0.7814 | 0.3515 | |
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| 0.6444 | 0.18 | 1000 | 0.5875 | 0.7769 | 0.3628 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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