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sentence-compression-roberta – AI Model by AlexMaclean | AlphaNeural AI
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AlexMaclean
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sentence-compression-roberta
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transformers
pytorch
roberta
token-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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sentence-compression-roberta
This model is a fine-tuned version of
roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3465
Accuracy: 0.8473
F1: 0.6835
Precision: 0.6835
Recall: 0.6835
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: 5e-05
train_batch_size: 16
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.5312
1.0
50
0.5251
0.7591
0.0040
0.75
0.0020
0.4
2.0
100
0.4003
0.8200
0.5341
0.7113
0.4275
0.3355
3.0
150
0.3465
0.8473
0.6835
0.6835
0.6835
Framework versions
Transformers 4.12.5
Pytorch 1.10.0+cu113
Datasets 1.16.1
Tokenizers 0.10.3
