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--- |
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license: cc-by-nc-sa-4.0 |
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base_model: InstaDeepAI/nucleotide-transformer-v2-100m-multi-species |
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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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- matthews_correlation |
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- accuracy |
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model-index: |
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- name: gut_1024b-finetuned-lora-v2-100m-multi-species |
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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_1024b-finetuned-lora-v2-100m-multi-species |
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This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-v2-100m-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-100m-multi-species) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5193 |
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- F1: 0.8251 |
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- Matthews Correlation: 0.5308 |
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- Accuracy: 0.7779 |
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- F1 Score: 0.8251 |
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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 | Matthews Correlation | Accuracy | F1 Score | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------:|:--------:|:--------:| |
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| 0.7015 | 0.02 | 100 | 0.6761 | 0.7478 | 0.0 | 0.5971 | 0.7478 | |
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| 0.7134 | 0.04 | 200 | 0.6272 | 0.7788 | 0.3129 | 0.6744 | 0.7788 | |
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| 0.6992 | 0.05 | 300 | 0.5981 | 0.7736 | 0.3943 | 0.7145 | 0.7736 | |
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| 0.6285 | 0.07 | 400 | 0.6951 | 0.7336 | 0.3658 | 0.6905 | 0.7336 | |
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| 0.6476 | 0.09 | 500 | 0.6052 | 0.7631 | 0.3673 | 0.7019 | 0.7631 | |
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| 0.5939 | 0.11 | 600 | 0.5809 | 0.7720 | 0.4050 | 0.7179 | 0.7720 | |
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| 0.5497 | 0.12 | 700 | 0.5403 | 0.8133 | 0.4867 | 0.7576 | 0.8133 | |
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| 0.5188 | 0.14 | 800 | 0.5580 | 0.7846 | 0.4694 | 0.7441 | 0.7846 | |
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| 0.546 | 0.16 | 900 | 0.5767 | 0.8041 | 0.4243 | 0.7154 | 0.8041 | |
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| 0.5705 | 0.18 | 1000 | 0.5193 | 0.8251 | 0.5308 | 0.7779 | 0.8251 | |
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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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