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citation_intent_classification_roberta_dapt – AI Model by ltuzova | AlphaNeural AI
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ltuzova
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citation_intent_classification_roberta_dapt
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
autotrain_compatible
endpoints_compatible
us
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citation_intent_classification_roberta_dapt
This model is a fine-tuned version of
ltuzova/cs_domain_pretrained_model
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.5175
Accuracy: 0.5108
F1 Macro: 0.1127
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: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 10
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1 Macro
1.6621
1.0
105
1.5071
0.5175
0.1137
1.4561
2.0
211
1.3867
0.5175
0.1137
1.4054
3.0
316
1.3482
0.5175
0.1137
1.3753
4.0
422
1.3319
0.5175
0.1137
Framework versions
Transformers 4.30.2
Pytorch 1.13.1+cu117
Datasets 2.13.2
Tokenizers 0.13.3
