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contemmcm/
846a866d5e830c5d9e01bdd6751cd56a

Name: 846a866d5e830c5d9e01bdd6751cd56a
Rating: 2.5 (8 reviews)

generated_from_trainer

studio-ousia/luke-japanese-large

finetune

apache-2.0

endpoints_compatible

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846a866d5e830c5d9e01bdd6751cd56a

This model is a fine-tuned version of studio-ousia/luke-japanese-large on the nyu-mll/glue [cola] dataset. It achieves the following results on the evaluation set:

Loss: 0.6215
Data Size: 1.0
Epoch Runtime: 50.3077
Accuracy: 0.6885
F1 Macro: 0.4078
Rouge1: 0.6895
Rouge2: 0.0
Rougel: 0.6885
Rougelsum: 0.6885

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	Rouge1	Rougel	Rougelsum
No log	0	0	0.7178	0	2.2685	0.3711	0.3519	0.3711	0.3701	0.3711
No log	1	267	0.6417	0.0078	3.4508	0.6885	0.4078	0.6895	0.6885	0.6885
No log	2	534	0.6363	0.0156	3.8059	0.6885	0.4078	0.6895	0.6885	0.6885
No log	3	801	0.6202	0.0312	5.1231	0.6885	0.4078	0.6895	0.6885	0.6885
No log	4	1068	0.6201	0.0625	7.0624	0.6885	0.4078	0.6895	0.6885	0.6885
0.0381	5	1335	0.6603	0.125	10.7459	0.6885	0.4078	0.6895	0.6885	0.6885
0.6168	6	1602	0.6563	0.25	16.8453	0.6885	0.4078	0.6895	0.6885	0.6885
0.6144	7	1869	0.6708	0.5	28.3367	0.6885	0.4078	0.6895	0.6885	0.6885
0.604	8.0	2136	0.6195	1.0	52.1877	0.6885	0.4078	0.6895	0.6885	0.6885
0.6096	9.0	2403	0.6451	1.0	49.7814	0.6885	0.4078	0.6895	0.6885	0.6885
0.6176	10.0	2670	0.6254	1.0	50.5146	0.6885	0.4078	0.6895	0.6885	0.6885
0.6203	11.0	2937	0.6220	1.0	49.2909	0.6885	0.4078	0.6895	0.6885	0.6885
0.6233	12.0	3204	0.6215	1.0	50.3077	0.6885	0.4078	0.6895	0.6885	0.6885

Framework versions

Transformers 4.57.0
Pytorch 2.8.0+cu128
Datasets 4.3.0
Tokenizers 0.22.1

contemmcm/846a866d5e830c5d9e01bdd6751cd56a

846a866d5e830c5d9e01bdd6751cd56a

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

contemmcm/
846a866d5e830c5d9e01bdd6751cd56a