QuantFactory/distilgpt2-finetuned-python_code_instructions_18k_alpaca-GGUF
This is quantized version of Vishaltiwari2019/distilgpt2-finetuned-python_code_instructions_18k_alpaca created using llama.cpp
Original Model Card
distilgpt2-finetuned-python_code_instructions_18k_alpaca
This model is a fine-tuned version of distilgpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5063
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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|
| 1.7264 | 1.0 | 3861 | 1.5890 |
| 1.6046 | 2.0 | 7722 | 1.5214 |
| 1.5359 | 3.0 | 11583 | 1.5063 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for QuantFactory/distilgpt2-finetuned-python_code_instructions_18k_alpaca-GGUF
Base model
distilbert/distilgpt2