mus_promoter-finetuned-lora-bert-base-lastln-t2t
This model is a fine-tuned version of AIRI-Institute/gena-lm-bert-base-lastln-t2t on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0934
- F1: 0.9867
- Mcc Score: 0.9683
- Accuracy: 0.9844
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 | Accuracy |
---|---|---|---|---|---|---|
0.3791 | 0.43 | 100 | 0.2575 | 0.9296 | 0.8460 | 0.9219 |
0.1329 | 0.85 | 200 | 0.0857 | 0.9730 | 0.9359 | 0.9688 |
0.1085 | 1.28 | 300 | 0.1337 | 0.9730 | 0.9359 | 0.9688 |
0.0609 | 1.71 | 400 | 0.1476 | 0.9730 | 0.9359 | 0.9688 |
0.041 | 2.14 | 500 | 0.0040 | 1.0 | 1.0 | 1.0 |
0.0165 | 2.56 | 600 | 0.0766 | 0.9863 | 0.9686 | 0.9844 |
0.0152 | 2.99 | 700 | 0.0908 | 0.9867 | 0.9683 | 0.9844 |
0.0087 | 3.42 | 800 | 0.0940 | 0.9730 | 0.9359 | 0.9688 |
0.0156 | 3.85 | 900 | 0.0911 | 0.9867 | 0.9683 | 0.9844 |
0.0081 | 4.27 | 1000 | 0.0934 | 0.9867 | 0.9683 | 0.9844 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for LiukG/mus_promoter-finetuned-lora-bert-base-lastln-t2t
Base model
AIRI-Institute/gena-lm-bert-base-lastln-t2t