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bert-base-cased-mnli-model1 – AI Model by varun-v-rao | AlphaNeural AI
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varun-v-rao
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bert-base-cased-mnli-model1
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-base-cased-mnli-model1
This model is a fine-tuned version of
bert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4700
Accuracy: 0.8367
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: 5
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.4755
1.0
6136
0.4356
0.8268
0.3597
2.0
12272
0.4384
0.8353
0.2668
3.0
18408
0.4700
0.8367
Framework versions
Transformers 4.35.2
Pytorch 2.1.1+cu121
Datasets 2.15.0
Tokenizers 0.15.0
