mt5-small-finetuned-17jan-1 – AI Model by mqy | AlphaNeural AI

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mt5-small-finetuned-17jan-1

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mt5-small-finetuned-17jan-1

This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.6637
Rouge1: 8.3942
Rouge2: 0.8333
Rougel: 8.2847
Rougelsum: 8.3183

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: 0.0001
train_batch_size: 10
eval_batch_size: 10
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
11.5311	1.0	60	3.3693	3.5755	0.6	3.6	3.5118
4.9804	2.0	120	2.9852	5.1928	0.9667	5.205	5.1941
4.0171	3.0	180	2.8622	5.8468	0.5889	5.9029	5.8766
3.7179	4.0	240	2.7056	8.4114	0.5	8.5056	8.4553
3.514	5.0	300	2.7171	9.3353	0.8333	9.2709	9.3029
3.4154	6.0	360	2.7082	8.6179	0.4167	8.5622	8.5483
3.3356	7.0	420	2.6801	8.3942	0.8333	8.2847	8.3183
3.3008	8.0	480	2.6757	8.2384	0.4167	8.1169	8.1087
3.2493	9.0	540	2.6646	8.2384	0.4167	8.1169	8.1087
3.2307	10.0	600	2.6637	8.3942	0.8333	8.2847	8.3183

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2