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roberta-large-sst2 – AI Model by philschmid | AlphaNeural AI
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philschmid
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roberta-large-sst2
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
glue
mit
model-index
autotrain_compatible
endpoints_compatible
us
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roberta-large-sst2
This model is a fine-tuned version of
roberta-large
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.1400
Accuracy: 0.9644
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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
distributed_type: sagemaker_data_parallel
num_devices: 8
total_train_batch_size: 256
total_eval_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.3688
1.0
264
0.1444
0.9564
0.1529
2.0
528
0.1502
0.9518
0.107
3.0
792
0.1388
0.9530
0.0666
4.0
1056
0.1400
0.9644
Framework versions
Transformers 4.17.0
Pytorch 1.10.2+cu113
Datasets 1.18.4
Tokenizers 0.11.6
