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distilbert-finetuned-mnli – AI Model by dzungever | AlphaNeural AI
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distilbert-finetuned-mnli
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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-finetuned-mnli
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: 0.7095
Accuracy: 0.8227
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: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5334
1.0
49088
0.5047
0.8026
0.3934
2.0
98176
0.5496
0.8199
0.3137
3.0
147264
0.7095
0.8227
Framework versions
Transformers 4.53.0
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2
