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bert-base-uncased-finetuned-mrpc-run_baseline_128 – AI Model by edademireleda | AlphaNeural AI
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edademireleda
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bert-base-uncased-finetuned-mrpc-run_baseline_128
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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bert-base-uncased-finetuned-mrpc-run_baseline_128
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.4531
Accuracy: 0.7797
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: 128
eval_batch_size: 128
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6026
1.0
29
0.5780
0.7083
0.5479
2.0
58
0.5083
0.7132
0.472
3.0
87
0.4656
0.7868
0.4198
4.0
116
0.4510
0.8137
0.3655
5.0
145
0.4351
0.8162
Framework versions
Transformers 4.57.2
Pytorch 2.9.0+cu126
Datasets 2.19.1
Tokenizers 0.22.1
