Downloads · 30 days
6
4% of all-time downloads
gemma-2-9b-CharacterCodex-qlora
cattoroboto/gemma-2-9b-CharacterCodex-qlora
gemma-2-9b-CharacterCodex-qlora is a machine learning model from cattoroboto. 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. The card lists the license as gemma.
All-time downloads
141
Public
Repo size
1.1 GB
Likes
1
Public
Repo makeup
Click a slice to open those files.
.pt434 MB · 38%
At a glance
- Library
- peft
- License
- gemma
- Model type
- gemma2
- Access
- Public
- Created
- Jul 2, 2024
- Updated
- Jul 2, 2024
- SHA
- f61ac1af
Base models
Datasets
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. --> <details><summary>See axolotl config</summary>This is a test qlora! 🙀
axolotl version: 0.4.1
base_model: google/gemma-2-9b
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
# huggingface repo
chat_template: gemma
datasets:
- path: NousResearch/CharacterCodex
type: completion
# chat_template: gemma
# drop_system_message: true
field: description
val_set_size: 0.0
output_dir: ./outputs/out
adapter: qlora
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
sequence_len: 2048
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch:
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
outputs/out
This model is a fine-tuned version of google/gemma-2-9b on the None dataset.
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: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 23
- num_epochs: 2
Training results
Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- Type
- gemma2
- License
- gemma
- Created
- Jul 2, 2024
- Updated
- Jul 2, 2024