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bert-base-cased-sft-glue-mrpc – AI Model by sauc-abadal-lloret | AlphaNeural AI
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sauc-abadal-lloret
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bert-base-cased-sft-glue-mrpc
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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-sft-glue-mrpc
This model is a fine-tuned version of
bert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3643
Accuracy: 0.8529
F1: 0.8929
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: 128
eval_batch_size: 128
seed: 42
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
F1
No log
0
0
0.7681
0.3162
0.0
No log
1.0
29
0.5222
0.7475
0.8413
No log
2.0
58
0.3570
0.8456
0.8840
No log
3.0
87
0.3643
0.8529
0.8929
Framework versions
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1
