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roberta-large-finetuned-clinc – AI Model by philschmid | AlphaNeural AI
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philschmid
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roberta-large-finetuned-clinc
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
clinc_oos
mit
model-index
autotrain_compatible
endpoints_compatible
us
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roberta-large-finetuned-clinc
This model is a fine-tuned version of
roberta-large
on the clinc_oos dataset. It achieves the following results on the evaluation set:
Loss: 0.2109
Accuracy: 0.9703
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: 128
eval_batch_size: 128
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: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
5.0643
1.0
120
5.0440
0.0065
4.2726
2.0
240
2.7488
0.7255
1.9687
3.0
360
0.8694
0.9174
0.5773
4.0
480
0.3267
0.9539
0.1842
5.0
600
0.2109
0.9703
Framework versions
Transformers 4.19.0.dev0
Pytorch 1.10.2+cu113
Datasets 1.18.4
Tokenizers 0.11.6
