flan-t5-base-da-multiwoz2.1_400-loss-ep100 – AI Model by Zekunli | AlphaNeural AI

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Zekunli/
flan-t5-base-da-multiwoz2.1_400-loss-ep100

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text2text-generation

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text-generation-inference

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flan-t5-base-da-multiwoz2.1_400-loss-ep100

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

Loss: 0.3730
Accuracy: 39.1491
Num: 7365
Gen Len: 16.1947

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: 80
seed: 1799
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Num	Gen Len
1.1193	2.33	400	0.5163	27.0396	7365	15.2292
0.5546	4.65	800	0.4312	33.6748	7365	16.0134
0.4799	6.98	1200	0.4032	34.9177	7365	15.8893
0.4377	9.3	1600	0.3886	36.8242	7365	15.6668
0.4107	11.63	2000	0.3822	36.8257	7365	16.5566
0.3868	13.95	2400	0.3771	38.1012	7365	16.2304
0.3695	16.28	2800	0.3738	38.9161	7365	15.9143
0.3524	18.6	3200	0.3730	39.1491	7365	16.1947
0.3417	20.93	3600	0.3767	40.0655	7365	15.9227
0.328	23.26	4000	0.3772	39.8485	7365	15.6276
0.3181	25.58	4400	0.3795	40.2318	7365	15.9794
0.3063	27.91	4800	0.3798	40.0663	7365	15.8098
0.2959	30.23	5200	0.3874	40.1586	7365	16.0183

Framework versions

Transformers 4.18.0
Pytorch 1.10.0+cu111
Datasets 2.5.1
Tokenizers 0.12.1