File size: 1,659 Bytes
f782f22 d2e7900 f782f22 3a19e5d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 |
# Llama-2-13b SuperCOT lora checkpoints
These are my Llama-2-13b SuperCOT Lora checkpoints trained using QLora on the [SuperCOT Dataset](https://huggingface.co/datasets/kaiokendev/SuperCOT-dataset).
### Architecture
- **Model Architecture**: Llama-2-13b
- **Training Algorithm**: QLora
### Training Details
- **Dataset**: [SuperCOT Dataset](https://huggingface.co/datasets/kaiokendev/SuperCOT-dataset)
- **Datset type**: alpaca
- **Training Parameters**: [See Here](https://github.com/OpenAccess-AI-Collective/axolotl/blob/main/examples/llama-2/qlora.yml)
- **Training Environment**: Axolotl
- **sequence_len**: 4096
## Acknowledgments
Special thanks to the creators of the datasets in SuperCOT. Additionally, thanks to Kaiokendev for curating the SuperCOT dataset. Thanks to the contributors of the Axolotl.
## Stuff generated from axolotl:
---
library_name: peft
---
## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions
- PEFT 0.5.0.dev0
- PEFT 0.5.0.dev0
|