t5-small-matthewKP – AI Model by rizvi-rahil786 | AlphaNeural AI

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t5-small-matthewKP

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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t5-small-matthewKP

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

Loss: 1.3587
Rouge1: 50.9483
Rouge2: 33.6216
Rougel: 50.8374
Rougelsum: 50.8405
Gen Len: 7.2358

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
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.1223	1.0	6162	1.3958	48.7571	32.9322	48.7201	48.6343	7.4432
1.0032	2.0	12324	1.3587	50.9483	33.6216	50.8374	50.8405	7.2358
0.9138	3.0	18486	1.4147	49.5295	30.0768	49.4184	49.4152	6.9196
0.8711	4.0	24648	1.3923	51.8423	33.5555	51.7412	51.706	6.9401
0.8407	5.0	30810	1.4422	50.9414	32.3617	50.8776	50.8806	6.9788
0.7328	6.0	36972	1.4904	50.7542	31.7725	50.6444	50.6829	6.9547
0.7564	7.0	43134	1.5097	49.922	30.9948	49.8255	49.8403	7.0006
0.7292	8.0	49296	1.5037	50.5598	31.1728	50.4433	50.4861	6.8773

Framework versions

Transformers 4.39.3
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2