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bert-large-mnli-3ep – AI Model by TehranNLP-org | AlphaNeural AI
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TehranNLP-org
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bert-large-mnli-3ep
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transformers
pytorch
bert
text-classification
generated_from_trainer
en
apache-2.0
autotrain_compatible
endpoints_compatible
us
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This model is a fine-tuned version of
bert-large-uncased
on the MNLI dataset. It achieves the following results on the evaluation set:
Loss: 0.5092
Accuracy: 0.8573
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: 5e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: not_parallel
gradient_accumulation_steps: 32
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2000
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.4736
1.0
12271
0.4213
0.8372
0.3248
2.0
24542
0.4055
0.8538
0.1571
3.0
36813
0.5092
0.8573
Framework versions
Transformers 4.17.0
Pytorch 1.10.0+cu113
Datasets 2.1.0
Tokenizers 0.11.6
