TAPT-V2-biomed_roberta_base – AI Model by Mardiyyah | AlphaNeural AI

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Mardiyyah/
TAPT-V2-biomed_roberta_base

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allenai/biomed_roberta_base

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TAPT-V2-biomed_roberta_base

This model is a fine-tuned version of allenai/biomed_roberta_base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 4.3766

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: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
6.8813	1.0	584	5.8254
5.616	2.0	1168	5.4221
5.2846	3.0	1752	5.0635
5.0121	4.0	2336	4.7765
4.814	5.0	2920	4.6518
4.6602	6.0	3504	4.5539
4.566	7.0	4088	4.4802
4.4826	8.0	4672	4.4628
4.4094	9.0	5256	4.3637
4.3667	10.0	5840	4.3197

Framework versions

Transformers 4.48.2
Pytorch 2.4.1+cu121
Datasets 3.0.2
Tokenizers 0.21.0