rtahmasbi / qlora-out

huggingface.co
Total runs: 0
24-hour runs: 0
7-day runs: 0
30-day runs: -2
Model's Last Updated: February 19 2025

Introduction of qlora-out

Model Details of qlora-out

Built with Axolotl

See axolotl config

axolotl version: 0.7.0

base_model: meta-llama/Llama-3.1-8B
# optionally might have model_type or tokenizer_type
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: rtahmasbi/data_ex1_FT
    type: alpaca
dataset_prepared_path:
val_set_size: 0
output_dir: ./outputs/qlora-out

adapter: qlora
lora_model_dir:

sequence_len: 15000
sample_packing: true
pad_to_sequence_len: true

lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  pad_token: "<|end_of_text|>"

outputs/qlora-out

This model is a fine-tuned version of meta-llama/Llama-3.1-8B on the rtahmasbi/data_ex1_FT 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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Use OptimizerNames.PAGED_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 10
  • num_epochs: 4.0
Training results
Framework versions
  • PEFT 0.14.0
  • Transformers 4.48.3
  • Pytorch 2.4.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0

Runs of rtahmasbi qlora-out on huggingface.co

0
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
-2
30-day runs

More Information About qlora-out huggingface.co Model

More qlora-out license Visit here:

https://choosealicense.com/licenses/llama3.1

qlora-out huggingface.co

qlora-out huggingface.co is an AI model on huggingface.co that provides qlora-out's model effect (), which can be used instantly with this rtahmasbi qlora-out model. huggingface.co supports a free trial of the qlora-out model, and also provides paid use of the qlora-out. Support call qlora-out model through api, including Node.js, Python, http.

rtahmasbi qlora-out online free

qlora-out huggingface.co is an online trial and call api platform, which integrates qlora-out's modeling effects, including api services, and provides a free online trial of qlora-out, you can try qlora-out online for free by clicking the link below.

rtahmasbi qlora-out online free url in huggingface.co:

https://huggingface.co/rtahmasbi/qlora-out

qlora-out install

qlora-out is an open source model from GitHub that offers a free installation service, and any user can find qlora-out on GitHub to install. At the same time, huggingface.co provides the effect of qlora-out install, users can directly use qlora-out installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

qlora-out install url in huggingface.co:

https://huggingface.co/rtahmasbi/qlora-out

Url of qlora-out

Provider of qlora-out huggingface.co

rtahmasbi
ORGANIZATIONS

Other API from rtahmasbi

huggingface.co

Total runs: 1
Run Growth: -1
Growth Rate: -100.00%
Updated:February 21 2025