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t5-small-ret-conceptnet2 – AI Model by shreyasharma | AlphaNeural AI
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t5-small-ret-conceptnet2
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transformers
pytorch
tensorboard
t5
text2text-generation
generated_from_trainer
apache-2.0
text-generation-inference
endpoints_compatible
us
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t5-small-ret-conceptnet2
This model is a fine-tuned version of
t5-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1709
Acc: {'accuracy': 0.8700980392156863}
Precision: {'precision': 0.811340206185567}
Recall: {'recall': 0.9644607843137255}
F1: {'f1': 0.8812989921612542}
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: 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: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Acc
Precision
Recall
F1
0.1989
1.0
721
0.1709
{'accuracy': 0.8700980392156863}
{'precision': 0.811340206185567}
{'recall': 0.9644607843137255}
{'f1': 0.8812989921612542}
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2
