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
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Model tree for gkteco/distillbert-finetuned-codesearchnet
Base model
distilbert/distilbert-base-uncased