SFT_shadow – AI Model by davidgaofc | AlphaNeural AI

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davidgaofc/
SFT_shadow

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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shadow

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

Loss: 1.2249
Rouge1: 0.2638
Rouge2: 0.1186
Rougel: 0.2171
Rougelsum: 0.2169
Gen Len: 146.8555

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.6504	1.0	718	1.5109	0.0112	0.0026	0.0098	0.0098	13.3183
1.7193	2.0	1436	1.3836	0.1697	0.0487	0.1355	0.1354	140.8933
1.5492	3.0	2154	1.3174	0.202	0.0564	0.1591	0.1592	153.2811
1.51	4.0	2872	1.2829	0.2152	0.0691	0.1708	0.1709	156.3921
1.4341	5.0	3590	1.2613	0.2336	0.0895	0.1866	0.1866	156.2713
1.4335	6.0	4308	1.2466	0.2534	0.1118	0.2073	0.2075	146.7207
1.4033	7.0	5026	1.2363	0.2591	0.1168	0.213	0.213	144.5354
1.4045	8.0	5744	1.2298	0.261	0.1171	0.2149	0.2149	147.7884
1.3839	9.0	6462	1.2260	0.263	0.1178	0.216	0.2159	147.3518
1.3863	10.0	7180	1.2249	0.2638	0.1186	0.2171	0.2169	146.8555

Framework versions

Transformers 4.35.2
Pytorch 2.1.1+cu121
Datasets 2.15.0
Tokenizers 0.15.0