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distilbert-base-uncased-finetuned-t_refund – AI Model by Gregorig | AlphaNeural AI
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Gregorig
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distilbert-base-uncased-finetuned-t_refund
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transformers
tensorboard
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased-finetuned-t_refund
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: 0.4303
Accuracy: 0.98
F1: 0.98
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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.6219
1.0
26
0.5846
0.88
0.9040
0.4025
2.0
52
0.3709
0.945
0.9506
0.1939
3.0
78
0.4010
0.975
0.9743
0.151
4.0
104
0.3797
0.965
0.9674
0.1117
5.0
130
0.4303
0.98
0.98
Framework versions
Transformers 4.41.1
Pytorch 2.3.0+cu121
Tokenizers 0.19.1
