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
- Downloads last month
- 287
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for QuantFactory/distilgpt2-finetuned-python_code_instructions_18k_alpaca-GGUF
Base model
distilbert/distilgpt2