You can deploy this model and start earning money today!

contemmcm/
51fc681a8bfda1a2bee4a1158398921d

Name: 51fc681a8bfda1a2bee4a1158398921d
Rating: 2.5 (7 reviews)

generated_from_trainer

studio-ousia/luke-large

finetune

apache-2.0

endpoints_compatible

Views

No views yet

51fc681a8bfda1a2bee4a1158398921d

This model is a fine-tuned version of studio-ousia/luke-large on the contemmcm/cls_mmlu dataset. It achieves the following results on the evaluation set:

Loss: 1.3936
Data Size: 0.25
Epoch Runtime: 25.8507
Accuracy: 0.2487
F1 Macro: 0.0996

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: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 32
total_eval_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Data Size	Epoch Runtime	Accuracy	F1 Macro
No log	0	0	1.3965	0	3.0460	0.2533	0.1011
No log	1	438	1.4000	0.0078	3.9178	0.2527	0.1008
No log	2	876	1.3893	0.0156	5.0310	0.2533	0.1011
No log	3	1314	1.3913	0.0312	7.0164	0.2533	0.1011
No log	4	1752	1.3989	0.0625	10.1487	0.2387	0.1066
0.0795	5	2190	1.3935	0.125	15.4329	0.2487	0.0996
0.1851	6	2628	1.3936	0.25	25.8507	0.2487	0.0996

Framework versions

Transformers 4.57.0
Pytorch 2.8.0+cu128
Datasets 4.3.0
Tokenizers 0.22.1

contemmcm/51fc681a8bfda1a2bee4a1158398921d

51fc681a8bfda1a2bee4a1158398921d

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

contemmcm/
51fc681a8bfda1a2bee4a1158398921d