Downloads · 30 days
7
2% of all-time downloads
AdvertLlama-7b
Around6827/AdvertLlama-7b
AdvertLlama-7b is a machine learning model from Around6827. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.
should probably proofread and complete it, then remove this comment. --
All-time downloads
397
Public
Repo size
42.6 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin13.8 GB · 100%
At a glance
- Library
- peft
- Model type
- llama
- Access
- Public
- Created
- Sep 28, 2023
- Updated
- Oct 3, 2023
- SHA
- 9016cba7
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
lora-out
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the None dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- 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:
- quant_method: bitsandbytes
- 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
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
Training results
Framework versions
- PEFT 0.6.0.dev0
- PEFT 0.6.0.dev0
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.7.1
- Tokenizers 0.14.0
- Library
- peft
- Type
- llama
- Created
- Sep 28, 2023
- Updated
- Oct 3, 2023