10pos_model – AI Model by jvalline | AlphaNeural AI

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jvalline/
10pos_model

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text2text-generation

generated_from_trainer

google-t5/t5-base

text-generation-inference

endpoints_compatible

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10pos_model

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

Loss: 0.3032
Bleu: 0.0001
Wer: 0.9323
Rougel: 0.1628
Gen Len: 18.9983

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: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Wer	Rougel	Gen Len
0.8158	0.16	1000	0.3327	0.0001	0.933	0.1616	18.999
0.3791	0.32	2000	0.3029	0.0001	0.9326	0.1623	18.9988
0.3536	0.48	3000	0.2901	0.0001	0.9325	0.1624	18.9988
0.3353	0.64	4000	0.2822	0.0001	0.9324	0.1626	18.9987
0.3333	0.8	5000	0.2774	0.0001	0.9323	0.1627	18.9987
0.3258	0.96	6000	0.2742	0.0001	0.9322	0.1627	18.9987
0.3267	1.12	7000	0.2811	0.0001	0.9323	0.1627	18.9984
0.3532	1.28	8000	0.2960	0.0001	0.9322	0.1629	18.9983
0.3859	1.44	9000	0.3083	0.0001	0.9323	0.1629	18.9983
0.3867	1.6	10000	0.3054	0.0001	0.9323	0.1628	18.9983
0.3807	1.76	11000	0.3038	0.0001	0.9323	0.1628	18.9983
0.3807	1.92	12000	0.3032	0.0001	0.9323	0.1628	18.9983

Framework versions

Transformers 4.37.1
Pytorch 2.3.0.dev20240122+cu121
Datasets 2.16.1
Tokenizers 0.15.1