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Mardiyyah/
cellate-tapt_freeze_llrd-LR_2e-05

Name: cellate-tapt_freeze_llrd-LR_2e-05
Availability: InStock

generated_from_trainer

Mardiyyah/biomedbert_model_extended_untrained

finetune

apache-2.0

endpoints_compatible

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cellate-tapt_freeze_llrd-LR_2e-05

This model is a fine-tuned version of Mardiyyah/biomedbert_model_extended_untrained on the Mardiyyah/TAPT_CeLLaTe1.0 dataset. It achieves the following results on the evaluation set:

Loss: 5.8892
Accuracy: 0.2761

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 3407
gradient_accumulation_steps: 2
total_train_batch_size: 32
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: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
10.1692	1.0	6	11.1264	0.0
9.9435	2.0	12	10.5601	0.0
9.3201	3.0	18	9.8066	0.0004
8.4869	4.0	24	8.8692	0.0080
7.8056	5.0	30	8.1258	0.0377
7.3126	6.0	36	7.8349	0.0633
6.9357	7.0	42	7.4240	0.0871
6.652	8.0	48	7.2423	0.1479
6.3972	9.0	54	6.9245	0.1860
6.2035	10.0	60	6.7783	0.2090
5.9674	11.0	66	6.5090	0.2233
5.8018	12.0	72	6.2905	0.2396
5.6325	13.0	78	6.1065	0.2698
5.581	14.0	84	6.0982	0.2694
5.4227	15.0	90	6.2502	0.2484
5.4131	16.0	96	5.9184	0.2669
5.726	16.7273	100	5.8348	0.2815

Framework versions

Transformers 4.48.2
Pytorch 2.4.1+cu121
Datasets 3.0.2
Tokenizers 0.21.0

Mardiyyah/cellate-tapt_freeze_llrd-LR_2e-05

cellate-tapt_freeze_llrd-LR_2e-05

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Mardiyyah/
cellate-tapt_freeze_llrd-LR_2e-05