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distillbert-fine-tuned-claimbuster3C – AI Model by rashmikamath01 | AlphaNeural AI
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distillbert-fine-tuned-claimbuster3C
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transformers
pytorch
distilbert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distillbert-fine-tuned-claimbuster3C
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: 0.4152
Accuracy: 0.8749
F1: 0.8748
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: 16
eval_batch_size: 16
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.3364
1.0
1177
0.3138
0.8659
0.8634
0.2366
2.0
2354
0.3200
0.8766
0.8764
0.1561
3.0
3531
0.4152
0.8749
0.8748
Framework versions
Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.2
