Total runs:
17
Run Growth:
-273
Growth Rate:
-1605.88%
Sponsored by
PostMcpAi
rtahmasbi / lora-r16-out-rasool
Model's Last Updated: February 20 2025
Introduction of lora-r16-out-rasool
Model Details of lora-r16-out-rasool
See axolotl config
axolotl version:
0.7.0
base_model: meta-llama/Llama-3.1-8B-Instruct
# 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: false
strict: false
datasets:
- path: rtahmasbi/data_ex1_FT
type: alpaca
dataset_prepared_path:
val_set_size: 0
output_dir: ./outputs/lora-r16-out-rasool
adapter: lora
lora_model_dir:
sequence_len: 15000
sample_packing: true
pad_to_sequence_len: true
lora_r: 16
lora_alpha: 8
lora_dropout: 0.0
lora_target_modules:
- q_proj
- v_proj
- o_proj
lora_fan_in_fan_out:
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 8
micro_batch_size: 2
num_epochs: 30
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/lora-r16-out-rasool
This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct 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: 8
- total_train_batch_size: 16
- 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: 30.0
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 lora-r16-out-rasool on huggingface.co
18
Total runs
0
24-hour runs
0
3-day runs
-127
7-day runs
-276
30-day runs
More Information About lora-r16-out-rasool huggingface.co Model
Url of lora-r16-out-rasool
lora-r16-out-rasool huggingface.co Url
Provider of lora-r16-out-rasool huggingface.co
Other API from rtahmasbi
Updated:February 21 2025
Total runs:
15
Run Growth:
-253
Growth Rate:
-1686.67%
Total runs:
4
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%