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distilbert_finetuned_claimdecomp – AI Model by gavulsim | AlphaNeural AI
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gavulsim
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distilbert_finetuned_claimdecomp
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transformers
pytorch
deberta
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert_finetuned_claimdecomp
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 9.3205
Accuracy: 0.335
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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 30000
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0064
50.0
5000
5.7963
0.375
0.0
100.0
10000
7.2917
0.36
0.0
150.0
15000
7.0473
0.33
0.0
200.0
20000
8.0988
0.31
0.0
250.0
25000
8.8824
0.325
0.0
300.0
30000
9.3205
0.335
Framework versions
Transformers 4.34.1
Pytorch 2.0.0
Datasets 2.14.5
Tokenizers 0.14.1
