Hugging Face's logo

sn56b1
/
814f19b2-e567-48bd-b878-462707019cfe

PEFT
Safetensors
llama
axolotl
Generated from Trainer
Model card Files Community
814f19b2-e567-48bd-b878-462707019cfe / README.md
TracyTank's picture
TracyTank
End of training
bc7e55b verified
preview code
|
raw
history blame contribute delete
4.34 kB
metadata
library_name: peft
license: llama3
base_model: MLP-KTLim/llama-3-Korean-Bllossom-8B
tags:
  - axolotl
  - generated_from_trainer
model-index:
  - name: 814f19b2-e567-48bd-b878-462707019cfe
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.4.1

adapter: lora
base_model: MLP-KTLim/llama-3-Korean-Bllossom-8B
bf16: true
chat_template: llama3
datasets:
- data_files:
  - 1b9657ed494e6d8c_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/1b9657ed494e6d8c_train_data.json
  type:
    field_instruction: tokens
    field_output: tags_skill
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: false
hub_model_id: sn56b1/814f19b2-e567-48bd-b878-462707019cfe
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 77GiB
max_steps: 100
micro_batch_size: 8
mlflow_experiment_name: /tmp/1b9657ed494e6d8c_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 25
save_strategy: steps
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: sn56-miner
wandb_mode: disabled
wandb_name: 814f19b2-e567-48bd-b878-462707019cfe
wandb_project: god
wandb_run: your_name
wandb_runid: 814f19b2-e567-48bd-b878-462707019cfe
warmup_steps: 10
weight_decay: 0.01
xformers_attention: false

814f19b2-e567-48bd-b878-462707019cfe

This model is a fine-tuned version of MLP-KTLim/llama-3-Korean-Bllossom-8B on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0290

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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 32
  • optimizer: Use OptimizerNames.ADAMW_TORCH 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
  • training_steps: 100

Training results

Training Loss Epoch Step Validation Loss
1.1718 0.0059 1 1.1031
0.3405 0.0534 9 0.1718
0.0523 0.1068 18 0.0547
0.0449 0.1602 27 0.0480
0.0495 0.2136 36 0.0413
0.0374 0.2671 45 0.0394
0.0466 0.3205 54 0.0346
0.0397 0.3739 63 0.0315
0.046 0.4273 72 0.0304
0.0245 0.4807 81 0.0299
0.0285 0.5341 90 0.0292
0.0303 0.5875 99 0.0290

Framework versions

  • PEFT 0.13.2
  • Transformers 4.46.0
  • Pytorch 2.5.0+cu124
  • Datasets 3.0.1
  • Tokenizers 0.20.1