mt5-small-task1-dataset1 – AI Model by ZhiguangHan | AlphaNeural AI

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ZhiguangHan/
mt5-small-task1-dataset1

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text2text-generation

generated_from_trainer

google/mt5-small

endpoints_compatible

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mt5-small-task1-dataset1

This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6492
Accuracy: 0.626

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: 5.6e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
10.2312	1.0	250	2.1246	0.194
2.2998	2.0	500	1.4171	0.194
1.6645	3.0	750	1.2718	0.206
1.4575	4.0	1000	1.1549	0.258
1.3335	5.0	1250	1.0267	0.432
1.1696	6.0	1500	0.8811	0.5
0.9974	7.0	1750	0.7960	0.532
0.9162	8.0	2000	0.7576	0.556
0.8463	9.0	2250	0.7342	0.588
0.8078	10.0	2500	0.6856	0.606
0.7751	11.0	2750	0.6655	0.612
0.7533	12.0	3000	0.6645	0.622
0.7337	13.0	3250	0.6625	0.62
0.7154	14.0	3500	0.6640	0.624
0.7038	15.0	3750	0.6492	0.626

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0