You can deploy this model and start earning money today!

contemmcm/
6a2530e6c868df18680f41c14d5ef6f0

Name: 6a2530e6c868df18680f41c14d5ef6f0
Rating: 2.5 (10 reviews)

generated_from_trainer

studio-ousia/mluke-base

finetune

apache-2.0

endpoints_compatible

Views

No views yet

6a2530e6c868df18680f41c14d5ef6f0

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

Loss: 0.6165
Data Size: 1.0
Epoch Runtime: 1143.7028
Accuracy: 0.7916
F1 Macro: 0.7923
Rouge1: 0.7913
Rouge2: 0.0
Rougel: 0.7916
Rougelsum: 0.7916

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	1.1016	0	8.4589	0.3288	0.1972	0.3290	0.3288	0.3290
1.1039	1	12271	1.0478	0.0078	18.3370	0.4819	0.4702	0.4821	0.4817	0.4817
0.833	2	24542	0.7488	0.0156	26.2226	0.6867	0.6845	0.6868	0.6868	0.6869
0.7266	3	36813	0.6842	0.0312	43.0689	0.7215	0.7178	0.7215	0.7214	0.7216
0.6783	4	49084	0.6413	0.0625	76.7296	0.7430	0.7426	0.7430	0.7431	0.7430
0.6121	5	61355	0.5804	0.125	143.1177	0.7653	0.7639	0.7653	0.7655	0.7652
0.5942	6	73626	0.6098	0.25	277.7222	0.7555	0.7558	0.7556	0.7555	0.7553
0.5069	7	85897	0.5428	0.5	568.1862	0.7815	0.7803	0.7814	0.7812	0.7816
0.4843	8.0	98168	0.5297	1.0	1148.5348	0.7963	0.7962	0.7962	0.7964	0.7962
0.4279	9.0	110439	0.5177	1.0	1145.6533	0.8040	0.8036	0.8041	0.8042	0.8041
0.3805	10.0	122710	0.5437	1.0	1141.6211	0.7984	0.7976	0.7984	0.7984	0.7984
0.3417	11.0	134981	0.5861	1.0	1141.4024	0.7929	0.7932	0.7929	0.7929	0.7928
0.2841	12.0	147252	0.6009	1.0	1143.8513	0.8018	0.8012	0.8016	0.8018	0.8017
0.3038	13.0	159523	0.6165	1.0	1143.7028	0.7916	0.7923	0.7913	0.7916	0.7916

Framework versions

Transformers 4.57.0
Pytorch 2.8.0+cu128
Datasets 4.3.0
Tokenizers 0.22.1

contemmcm/6a2530e6c868df18680f41c14d5ef6f0

6a2530e6c868df18680f41c14d5ef6f0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

contemmcm/
6a2530e6c868df18680f41c14d5ef6f0