seq2sparql – AI Model by mglaser99 | AlphaNeural AI

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mglaser99/
seq2sparql

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text2text-generation

generated_from_trainer

google-t5/t5-base

text-generation-inference

endpoints_compatible

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seq2sparql

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

Loss: nan
Rouge1: 0.0
Rouge2: 0.0
Rougel: 0.0
Rougelsum: 0.0
Gen Len: 0.0

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: 4e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.3521	0.08	1000	0.1646	32.2799	27.7633	32.293	32.2772	19.0
0.1979	0.15	2000	nan	0.0	0.0	0.0	0.0	0.0
0.0	0.23	3000	nan	0.0	0.0	0.0	0.0	0.0
0.0	0.31	4000	nan	0.0	0.0	0.0	0.0	0.0
0.0	0.38	5000	nan	0.0	0.0	0.0	0.0	0.0
0.0	0.46	6000	nan	0.0	0.0	0.0	0.0	0.0
0.0	0.54	7000	nan	0.0	0.0	0.0	0.0	0.0
0.0	0.62	8000	nan	0.0	0.0	0.0	0.0	0.0
0.0	0.69	9000	nan	0.0	0.0	0.0	0.0	0.0
0.0	0.77	10000	nan	0.0	0.0	0.0	0.0	0.0
0.0	0.85	11000	nan	0.0	0.0	0.0	0.0	0.0
0.0	0.92	12000	nan	0.0	0.0	0.0	0.0	0.0
0.0	1.0	13000	nan	0.0	0.0	0.0	0.0	0.0

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1