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distillbert-finetuned-codesearchnet – AI Model by gkteco | AlphaNeural AI
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distillbert-finetuned-codesearchnet
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transformers
tensorboard
safetensors
distilbert
fill-mask
generated_from_trainer
code_search_net
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distillbert-finetuned-codesearchnet
This model is a fine-tuned version of
distilbert-base-uncased
on the code_search_net dataset. It achieves the following results on the evaluation set:
Loss: 1.2471
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
1.5595
1.0
7334
1.3620
1.3167
2.0
14668
1.2724
1.2549
3.0
22002
1.2471
Framework versions
Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
