santacoder-finetuned-xlcost-python
This model is a fine-tuned version of bigcode/santacoder on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4779
Model description
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Intended uses & limitations
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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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 5000
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.6748 | 0.1 | 500 | 0.8333 |
0.3933 | 0.2 | 1000 | 0.9118 |
0.2243 | 0.3 | 1500 | 1.0523 |
0.1497 | 0.4 | 2000 | 1.1595 |
0.1099 | 0.5 | 2500 | 1.2568 |
0.0852 | 0.6 | 3000 | 1.2997 |
0.0761 | 0.7 | 3500 | 1.3693 |
0.0757 | 0.8 | 4000 | 1.3683 |
0.0545 | 0.9 | 4500 | 1.4053 |
0.0634 | 1.0 | 5000 | 1.4150 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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