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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: AIRI-Institute/gena-lm-bert-large-t2t
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - accuracy
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+ model-index:
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+ - name: gena-lm-bert-large-t2t_ft_BioS74_1kbpHG19_DHSs_H3K27AC_one_shot
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+ results: []
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+ ---
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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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+
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+ # gena-lm-bert-large-t2t_ft_BioS74_1kbpHG19_DHSs_H3K27AC_one_shot
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+
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+ This model is a fine-tuned version of [AIRI-Institute/gena-lm-bert-large-t2t](https://huggingface.co/AIRI-Institute/gena-lm-bert-large-t2t) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9119
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+ - F1 Score: 0.6842
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+ - Precision: 0.7222
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+ - Recall: 0.65
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+ - Accuracy: 0.6842
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+ - Auc: 0.7528
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+ - Prc: 0.8171
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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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+ - num_epochs: 20
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Score | Precision | Recall | Accuracy | Auc | Prc |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:------:|:------:|
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+ | 0.4776 | 13.1579 | 500 | 0.9119 | 0.6842 | 0.7222 | 0.65 | 0.6842 | 0.7528 | 0.8171 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.0.dev0
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.20.0
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