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thrunlab/t5-large_cola_dense_epochs-7_decoder_all_sparsity10

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face

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t5-largecoladenseepochs-7decoderallsparsity10

This model is a fine-tuned version of t5-large on the glue dataset. It achieves the following results on the evaluation set:

—Loss: 4.6969
—Accuracy: 0.8380

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
—trainbatchsize: 64
—evalbatchsize: 128
—seed: 1
—distributed_type: multi-GPU
—gradientaccumulationsteps: 2
—totaltrainbatch_size: 128
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—lrschedulerwarmup_steps: 20
—num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5441	0.37	25	0.5813	0.6913
0.3969	0.75	50	0.5219	0.8044
0.3537	1.12	75	0.4713	0.8313
0.2905	1.49	100	0.6308	0.8150
0.3157	1.87	125	0.4301	0.8341
0.2208	2.24	150	2.3147	0.8332
0.2231	2.61	175	0.4612	0.8341
0.2404	2.99	200	1.5471	0.8265
0.1697	3.36	225	0.8701	0.8313
0.131	3.73	250	1.2642	0.8380
0.1219	4.1	275	0.9926	0.8370
0.2647	4.48	300	5.1919	0.8341
0.1329	4.85	325	2.2726	0.8418
0.0857	5.22	350	4.2193	0.8370
0.0989	5.6	375	5.3604	0.8389
0.2557	5.97	400	3.0246	0.8341
0.2617	6.34	425	5.6630	0.8456
0.2526	6.72	450	6.0474	0.8360

Framework versions

—Transformers 4.34.1
—Pytorch 2.0.1+cu117
—Datasets 2.9.0
—Tokenizers 0.14.1