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nli-finetune-model – AI Model by underfit | AlphaNeural AI
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nli-finetune-model
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
multi_nli
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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nli-finetune-model
This model is a fine-tuned version of
bert-large-uncased
on the multi_nli dataset. It achieves the following results on the evaluation set:
Loss: 1.2551
Accuracy: 0.7793
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: 1e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6813
1.0
2500
0.6655
0.7657
0.5632
2.0
5000
1.0409
0.778
0.3753
3.0
7500
1.2551
0.7793
Framework versions
Transformers 4.28.0
Pytorch 1.13.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3
