afg1
/

pombe_curation_fold_0

Text Classification

Generated from Trainer

Eval Results (legacy)

text-embeddings-inference

Model card Files Files and versions

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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Safetensors

Model size

0.1B params

Tensor type

F32

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Model tree for afg1/pombe_curation_fold_0

Base model

microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext

Finetuned

(168)

this model

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Evaluation results

Accuracy on afg1/pombe-canto-data
test set self-reported

0.925
Recall on afg1/pombe-canto-data
test set self-reported

0.937
Precision on afg1/pombe-canto-data
test set self-reported

0.914
F1 on afg1/pombe-canto-data
test set self-reported

0.925
Total_Time_In_Seconds on afg1/pombe-canto-data
test set self-reported

118.326
Samples_Per_Second on afg1/pombe-canto-data
test set self-reported

21.889
Latency_In_Seconds on afg1/pombe-canto-data
test set self-reported

0.046