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distilbert-base-uncased-finetuned-mnli – AI Model by mikemosc | AlphaNeural AI
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mikemosc
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distilbert-base-uncased-finetuned-mnli
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
glue
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased-finetuned-mnli
This model is a fine-tuned version of
distilbert-base-uncased
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.5546
Accuracy: 0.8188
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
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5153
1.0
24544
0.4999
0.8029
0.4194
2.0
49088
0.4788
0.8138
0.3065
3.0
73632
0.5546
0.8188
0.2172
4.0
98176
0.7237
0.8142
0.1784
5.0
122720
0.8463
0.8165
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
