gut_1024-finetuned-lora-NT-500m-1000g
This model is a fine-tuned version of InstaDeepAI/nucleotide-transformer-500m-1000g on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4974
- F1: 0.8222
- Mcc Score: 0.5121
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Mcc Score |
---|---|---|---|---|---|
0.81 | 0.02 | 100 | 0.6937 | 0.7478 | 0.0 |
0.7437 | 0.04 | 200 | 0.9181 | 0.0 | 0.0 |
0.7256 | 0.05 | 300 | 0.6935 | 0.7478 | 0.0 |
0.6717 | 0.07 | 400 | 0.6097 | 0.7208 | 0.3287 |
0.6583 | 0.09 | 500 | 0.6723 | 0.6032 | 0.3371 |
0.6158 | 0.11 | 600 | 0.5444 | 0.7973 | 0.4579 |
0.5618 | 0.12 | 700 | 0.5551 | 0.7728 | 0.4420 |
0.5324 | 0.14 | 800 | 0.5200 | 0.7764 | 0.4601 |
0.5326 | 0.16 | 900 | 0.5166 | 0.8190 | 0.4874 |
0.5769 | 0.18 | 1000 | 0.4974 | 0.8222 | 0.5121 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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