pombe_curation_fold_0
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on an unknown dataset.
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.42.3
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Evaluation results
- Accuracy on afg1/pombe-canto-datatest set self-reported0.925
- Recall on afg1/pombe-canto-datatest set self-reported0.937
- Precision on afg1/pombe-canto-datatest set self-reported0.914
- F1 on afg1/pombe-canto-datatest set self-reported0.925
- Total_Time_In_Seconds on afg1/pombe-canto-datatest set self-reported118.326
- Samples_Per_Second on afg1/pombe-canto-datatest set self-reported21.889
- Latency_In_Seconds on afg1/pombe-canto-datatest set self-reported0.046