flan-t5-large-da-multiwoz2.0_400-ep20-nonstop – AI Model by Zekunli | AlphaNeural AI

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Zekunli/
flan-t5-large-da-multiwoz2.0_400-ep20-nonstop

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flan-t5-large-da-multiwoz2.0_400-ep20-nonstop

This model is a fine-tuned version of google/flan-t5-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3661
Accuracy: 41.2421
Num: 7358
Gen Len: 15.5222

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: 2e-05
train_batch_size: 16
eval_batch_size: 64
seed: 1799
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Num	Gen Len
1.1824	1.16	200	0.5187	28.4524	7358	14.7642
0.5471	2.33	400	0.4278	32.5629	7358	15.4386
0.4647	3.49	600	0.4029	35.2443	7358	16.135
0.4313	4.65	800	0.3820	36.6479	7358	16.1552
0.4074	5.81	1000	0.3775	37.6957	7358	15.1439
0.3859	6.98	1200	0.3690	38.3142	7358	15.2045
0.369	8.14	1400	0.3720	39.8799	7358	15.7923
0.3547	9.3	1600	0.3665	39.5217	7358	15.3394
0.3457	10.47	1800	0.3632	39.8289	7358	15.4761
0.3423	11.63	2000	0.3678	39.9509	7358	15.6708
0.3295	12.79	2200	0.3657	41.1373	7358	15.1586
0.3212	13.95	2400	0.3651	40.8611	7358	15.7312
0.3128	15.12	2600	0.3664	40.8806	7358	15.4553
0.3131	16.28	2800	0.3677	40.8906	7358	15.4629
0.3093	17.44	3000	0.3661	40.9971	7358	15.4329
0.3021	18.6	3200	0.3652	41.2953	7358	15.5118
0.3004	19.77	3400	0.3661	41.2492	7358	15.5246

Framework versions

Transformers 4.18.0
Pytorch 1.10.0+cu111
Datasets 2.5.1
Tokenizers 0.12.1