metadata
library_name: peft
license: llama3.1
base_model: unsloth/Llama-3.1-Storm-8B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 8b6619f1-e8e2-4475-a003-33211e86f690
results: []
See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: unsloth/Llama-3.1-Storm-8B
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- b51894bc358e69ef_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/b51894bc358e69ef_train_data.json
type:
field_instruction: question_en
field_output: chosen_en
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 30
eval_max_new_tokens: 128
eval_steps: 50
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 16
gradient_checkpointing: true
group_by_length: false
hub_model_id: Romain-XV/8b6619f1-e8e2-4475-a003-33211e86f690
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
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: true
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
lr_scheduler: cosine
micro_batch_size: 4
mlflow_experiment_name: /tmp/b51894bc358e69ef_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 2048
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 80865761-d38a-4c48-9ea1-fb8848e26565
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 80865761-d38a-4c48-9ea1-fb8848e26565
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
8b6619f1-e8e2-4475-a003-33211e86f690
This model is a fine-tuned version of unsloth/Llama-3.1-Storm-8B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1177
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0186 | 0.0008 | 1 | 2.0494 |
| 1.4436 | 0.0406 | 50 | 1.3902 |
| 1.2774 | 0.0812 | 100 | 1.3402 |
| 1.3279 | 0.1218 | 150 | 1.3092 |
| 1.2515 | 0.1625 | 200 | 1.2914 |
| 1.2672 | 0.2031 | 250 | 1.2785 |
| 1.2416 | 0.2437 | 300 | 1.2647 |
| 1.2159 | 0.2843 | 350 | 1.2555 |
| 1.1702 | 0.3249 | 400 | 1.2434 |
| 1.2178 | 0.3655 | 450 | 1.2364 |
| 1.3226 | 0.4062 | 500 | 1.2286 |
| 1.1198 | 0.4468 | 550 | 1.2208 |
| 1.2484 | 0.4874 | 600 | 1.2148 |
| 1.1048 | 0.5280 | 650 | 1.2099 |
| 1.2055 | 0.5686 | 700 | 1.2041 |
| 1.219 | 0.6092 | 750 | 1.1982 |
| 1.2205 | 0.6498 | 800 | 1.1918 |
| 1.275 | 0.6905 | 850 | 1.1856 |
| 1.1738 | 0.7311 | 900 | 1.1803 |
| 1.1674 | 0.7717 | 950 | 1.1752 |
| 1.1784 | 0.8123 | 1000 | 1.1705 |
| 1.1904 | 0.8529 | 1050 | 1.1673 |
| 1.1293 | 0.8935 | 1100 | 1.1626 |
| 1.1344 | 0.9342 | 1150 | 1.1571 |
| 1.1763 | 0.9748 | 1200 | 1.1534 |
| 1.0566 | 1.0154 | 1250 | 1.1584 |
| 1.0529 | 1.0560 | 1300 | 1.1588 |
| 1.1357 | 1.0966 | 1350 | 1.1547 |
| 1.0739 | 1.1372 | 1400 | 1.1519 |
| 0.9531 | 1.1778 | 1450 | 1.1495 |
| 1.0049 | 1.2185 | 1500 | 1.1456 |
| 0.9675 | 1.2591 | 1550 | 1.1431 |
| 0.9961 | 1.2997 | 1600 | 1.1408 |
| 0.9481 | 1.3403 | 1650 | 1.1355 |
| 0.9777 | 1.3809 | 1700 | 1.1339 |
| 1.031 | 1.4215 | 1750 | 1.1327 |
| 1.0313 | 1.4622 | 1800 | 1.1315 |
| 0.932 | 1.5028 | 1850 | 1.1272 |
| 1.003 | 1.5434 | 1900 | 1.1260 |
| 1.0032 | 1.5840 | 1950 | 1.1236 |
| 0.913 | 1.6246 | 2000 | 1.1231 |
| 0.9941 | 1.6652 | 2050 | 1.1222 |
| 0.9415 | 1.7058 | 2100 | 1.1204 |
| 1.0222 | 1.7465 | 2150 | 1.1188 |
| 0.9803 | 1.7871 | 2200 | 1.1183 |
| 0.9454 | 1.8277 | 2250 | 1.1181 |
| 0.988 | 1.8683 | 2300 | 1.1182 |
| 0.9538 | 1.9089 | 2350 | 1.1179 |
| 0.9843 | 1.9495 | 2400 | 1.1179 |
| 0.8832 | 1.9902 | 2450 | 1.1177 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1