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OTAR3088/
CeLLaTe3.0_Base_with_vague_adapted_pubmed_bert

Name: CeLLaTe3.0_Base_with_vague_adapted_pubmed_bert
Availability: InStock

generated_from_trainer

Mardiyyah/cellate2.0-tapt_base-LR_5e-05

finetune

mit

endpoints_compatible

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CeLLaTe3.0_Base_with_vague_adapted_pubmed_bert

This model is a fine-tuned version of Mardiyyah/cellate2.0-tapt_base-LR_5e-05 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1738
Precision: 0.7469
Recall: 0.8402
F1: 0.7908
Accuracy: 0.9639

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: 32
eval_batch_size: 16
seed: 3407
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.3921	1.0	101	0.5023	0.3694	0.0207	0.0393	0.8661
0.2951	2.0	202	0.1611	0.6429	0.7769	0.7036	0.9593
0.1307	3.0	303	0.1510	0.7074	0.7901	0.7465	0.9616
0.0893	4.0	404	0.1472	0.7262	0.8118	0.7667	0.9631
0.0669	5.0	505	0.1802	0.6627	0.7951	0.7229	0.9565
0.0507	6.0	606	0.1758	0.7469	0.8402	0.7908	0.9639
0.0395	7.0	707	0.1806	0.7347	0.8361	0.7821	0.9634
0.0328	8.0	808	0.1954	0.7293	0.8093	0.7672	0.9632
0.0282	9.0	909	0.2014	0.7426	0.8083	0.7740	0.9622

Framework versions

Transformers 4.48.2
Pytorch 2.4.1+cu121
Datasets 3.0.2
Tokenizers 0.21.0

OTAR3088/CeLLaTe3.0_Base_with_vague_adapted_pubmed_bert

CeLLaTe3.0_Base_with_vague_adapted_pubmed_bert

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

OTAR3088/
CeLLaTe3.0_Base_with_vague_adapted_pubmed_bert