library_name: peft
datasets:
- b-mc2/sql-create-context
language:
- en
metrics:
- rouge
pipeline_tag: question-answering
license: apache-2.0
tags:
- SQL
- PEFT
- GPT
- GPT2-Medium
- Question& Answer
GPT-2 Medium
Model Details
Model Description: GPT-2 Medium is the 355M parameter version of GPT-2, a transformer-based language model created and released by OpenAI. The model is a pretrained model on English language using a causal language modeling (CLM) objective.
Parameter-Efficient Fine-tuning (PEFT)
Parameter-Efficient Fine-tuning (PEFT) is a technique used to improve the performance of pre-trained language models (LLMs) on specific downstream tasks without fine-tuning all the model's parameters. This is done by freezing most of the model's parameters and only fine-tuning a small number of parameters that are specific to the downstream task.
Training Data
the model is trained on 'b-mc2/sql-create-context' dataset upto 5000rows
Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- 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: float16
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- 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: float16
Framework versions
PEFT 0.5.0
PEFT 0.5.0