pegasus_trained_SIR

marij868/pegasus_trained_SIR

pegasus_trained_SIR is a machine learning model from marij868. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.

probably proofread and complete it, then remove this comment. --

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At a glance

Library: transformers
Model type: pegasus
Access: Public
Created: Apr 12, 2023
Updated: Apr 13, 2023
SHA: d91a63df

Model card

From the Hugging Face model README

pegasus_trained_SIR

This model is a fine-tuned version of google/pegasus-large on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 1.0036
Train Sparse Categorical Accuracy: 0.7945
Validation Loss: 1.1063
Validation Sparse Categorical Accuracy: 0.7936
Epoch: 2

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:

optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32

Training results

Train Loss	Train Sparse Categorical Accuracy	Validation Loss	Validation Sparse Categorical Accuracy	Epoch
1.3170	0.7603	1.1221	0.7874	0
1.1244	0.7805	1.1193	0.7913	1
1.0036	0.7945	1.1063	0.7936	2

Framework versions

Transformers 4.28.0
TensorFlow 2.12.0
Datasets 2.11.0
Tokenizers 0.13.3

Library: transformers
Type: pegasus
Created: Apr 12, 2023
Updated: Apr 13, 2023