50pos_model – AI Model by jvalline | AlphaNeural AI

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jvalline/
50pos_model

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text2text-generation

generated_from_trainer

google-t5/t5-base

text-generation-inference

endpoints_compatible

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50pos_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: 1.4089
Bleu: 0.0001
Wer: 0.9459
Rougel: 0.1326
Gen Len: 18.9987

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
2.191	0.16	1000	1.3669	0.0001	0.9468	0.1309	18.999
1.5151	0.32	2000	1.2748	0.0001	0.9458	0.1327	18.9987
1.6193	0.48	3000	1.4301	0.0001	0.9457	0.133	18.9986
1.7458	0.64	4000	1.4091	0.0001	0.9459	0.1326	18.9986
1.7281	0.8	5000	1.4088	0.0001	0.9459	0.1326	18.9986
1.7255	0.96	6000	1.4089	0.0001	0.9459	0.1326	18.9986
1.7297	1.12	7000	1.4089	0.0001	0.9459	0.1326	18.9987
1.7197	1.28	8000	1.4089	0.0001	0.9459	0.1326	18.9987
1.7287	1.44	9000	1.4088	0.0001	0.9459	0.1326	18.9986
1.7253	1.6	10000	1.4088	0.0001	0.9459	0.1326	18.9987
1.7189	1.76	11000	1.4089	0.0001	0.9459	0.1326	18.9987
1.7257	1.92	12000	1.4089	0.0001	0.9459	0.1326	18.9987

Framework versions

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