You can deploy this model and start earning money today!

contemmcm/
3ba0289a98a5677344bb92be93321ea5

Name: 3ba0289a98a5677344bb92be93321ea5
Rating: 2.5 (7 reviews)

Views

No views yet

3ba0289a98a5677344bb92be93321ea5

This model is a fine-tuned version of distilbert/distilbert-base-uncased-distilled-squad on the nyu-mll/glue [sst2] dataset. It achieves the following results on the evaluation set:

More information needed

More information needed

More information needed

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 Loss	Epoch	Step	Validation Loss	Data Size	Epoch Runtime	Accuracy	F1 Macro	Rouge1	Rougel	Rougelsum
No log	0	0	0.6993	0	0.8597	0.4919	0.3317	0.4919	0.4919	0.4931
No log	1	2104	0.5808	0.0078	1.8249	0.7963	0.7960	0.7963	0.7963	0.7963
No log	2	4208	0.4219	0.0156	1.7817	0.8056	0.8031	0.8044	0.8056	0.8056
0.0096	3	6312	0.3745	0.0312	2.7260	0.8368	0.8356	0.8368	0.8368	0.8368
0.3284	4	8416	0.2913	0.0625	4.4461	0.8692	0.8692	0.8692	0.8692	0.8692
0.2645	5	10520	0.2758	0.125	7.7715	0.8681	0.8680	0.8681	0.8681	0.8681
0.1971	6	12624	0.2813	0.25	14.3866	0.8889	0.8885	0.8889	0.8889	0.8889
0.1695	7	14728	0.3693	0.5	27.3830	0.8877	0.8871	0.8877	0.8877	0.8877
0.1588	8.0	16832	0.2904	1.0	53.1959	0.8924	0.8923	0.8924	0.8924	0.8924
0.1085	9.0	18936	0.3801	1.0	55.1059	0.8935	0.8934	0.8947	0.8935	0.8935