metadata
library_name: transformers
base_model: AIRI-Institute/gena-lm-bert-base-t2t-multi
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: gena-lm-bert-base-t2t-multi_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot
results: []
gena-lm-bert-base-t2t-multi_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot
This model is a fine-tuned version of AIRI-Institute/gena-lm-bert-base-t2t-multi on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5976
- F1 Score: 0.7887
- Precision: 0.7368
- Recall: 0.8485
- Accuracy: 0.7458
- Auc: 0.7949
- Prc: 0.8250
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Score | Precision | Recall | Accuracy | Auc | Prc |
|---|---|---|---|---|---|---|---|---|---|
| 0.6969 | 8.3333 | 500 | 0.6487 | 0.7077 | 0.7188 | 0.6970 | 0.6780 | 0.7523 | 0.7272 |
| 0.6553 | 16.6667 | 1000 | 0.5976 | 0.7887 | 0.7368 | 0.8485 | 0.7458 | 0.7949 | 0.8250 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.18.0
- Tokenizers 0.20.0