End of training

README.md

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+---
+base_model: zhihan1996/DNABERT-2-117M
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+model-index:
+- name: DNABERT-2-117M_ft_Hepg2_1kbpHG19_DHSs_H3K27AC
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# DNABERT-2-117M_ft_Hepg2_1kbpHG19_DHSs_H3K27AC
+
+This model is a fine-tuned version of [zhihan1996/DNABERT-2-117M](https://huggingface.co/zhihan1996/DNABERT-2-117M) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4809
+- F1 Score: 0.8080
+- Precision: 0.7661
+- Recall: 0.8546
+- Accuracy: 0.7770
+- Mcc Score: 0.5487
+- Roc Auc Score: 0.7686
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | F1 Score | Precision | Recall | Accuracy | Mcc Score | Roc Auc Score |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:---------:|:-------------:|
+| 0.4948        | 1.4881 | 500  | 0.5034          | 0.7825   | 0.7980    | 0.7677 | 0.7658   | 0.5296    | 0.7656        |
+| 0.4623        | 2.9762 | 1000 | 0.4809          | 0.8080   | 0.7661    | 0.8546 | 0.7770   | 0.5487    | 0.7686        |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.3.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.0