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NLP_sequences_example – AI Model by EdwarV | AlphaNeural AI | AlphaNeural AI
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NLP_sequences_example
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
glue
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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NLP_sequences_example
This model is a fine-tuned version of
distilroberta-base
on the glue and the mrpc datasets. It achieves the following results on the evaluation set:
Loss: 0.6412
Accuracy: 0.6649
F1: 0.7987
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: 0.0002
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.6576
1.09
500
0.6249
0.6838
0.8122
0.6424
2.18
1000
0.6427
0.6838
0.8122
Framework versions
Transformers 4.29.0
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.13.3
