tensorboard region:us
## OVERVIEW
PEFT model trained on a strided, raw text dataset. 
Full training parameters are available in training_parameters.json.
The most salient model feature is a training context window of 1024 tokens, with each training window overlapped with the last 128 tokens of the previous window.
This overlap ratio is unusual and produces objectionable quantitative results in perplexity eval.

---
library_name: peft
---
## Training procedure


The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: True
- load_in_4bit: False
- 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: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32

The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: True
- load_in_4bit: False
- 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: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
### Framework versions

- PEFT 0.5.0.dev0

- PEFT 0.5.0.dev0
