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--- |
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license: cc-by-nc-sa-4.0 |
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base_model: InstaDeepAI/nucleotide-transformer-v2-250m-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-v2-250m-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-v2-250m-multi-species |
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This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-v2-250m-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-250m-multi-species) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4815 |
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- F1: 0.8414 |
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- Matthews Correlation: 0.5610 |
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- Accuracy: 0.7880 |
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- F1 Score: 0.8414 |
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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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| 0.682 | 0.02 | 100 | 0.5545 | 0.8132 | 0.4597 | 0.7369 | 0.8132 | |
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| 0.6379 | 0.04 | 200 | 0.6119 | 0.7498 | 0.4244 | 0.7154 | 0.7498 | |
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| 0.5973 | 0.05 | 300 | 0.5226 | 0.8221 | 0.5154 | 0.7707 | 0.8221 | |
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| 0.5451 | 0.07 | 400 | 0.5159 | 0.8244 | 0.5010 | 0.7521 | 0.8244 | |
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| 0.5538 | 0.09 | 500 | 0.5538 | 0.8102 | 0.5043 | 0.7648 | 0.8102 | |
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| 0.549 | 0.11 | 600 | 0.5220 | 0.8258 | 0.5188 | 0.7715 | 0.8258 | |
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| 0.4887 | 0.12 | 700 | 0.4940 | 0.8330 | 0.5317 | 0.7728 | 0.8330 | |
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| 0.4893 | 0.14 | 800 | 0.4951 | 0.8352 | 0.5519 | 0.7872 | 0.8352 | |
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| 0.4794 | 0.16 | 900 | 0.5008 | 0.8443 | 0.5687 | 0.7893 | 0.8443 | |
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| 0.5437 | 0.18 | 1000 | 0.4815 | 0.8414 | 0.5610 | 0.7880 | 0.8414 | |
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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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