metadata
library_name: peft
license: llama3
base_model: Eurdem/Defne_llama3_2x8B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 05a9f7dd-900b-4001-b2ea-acd57578d12c
results: []
See axolotl config
axolotl version: 0.4.1
adapter: lora
auto_find_batch_size: true
base_model: Eurdem/Defne_llama3_2x8B
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 156edcd3af986b55_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/156edcd3af986b55_train_data.json
type:
field_input: input
field_instruction: instruction
field_output: output
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
do_eval: true
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 50
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: false
group_by_length: true
hub_model_id: lesso06/05a9f7dd-900b-4001-b2ea-acd57578d12c
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.000206
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 128
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 500
micro_batch_size: 4
mlflow_experiment_name: /tmp/G.O.D/156edcd3af986b55_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
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: 50
saves_per_epoch: null
sequence_len: 512
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: 8a53a0cc-26c6-46e3-98ec-23ad710799e9
wandb_project: 06a
wandb_run: your_name
wandb_runid: 8a53a0cc-26c6-46e3-98ec-23ad710799e9
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null
05a9f7dd-900b-4001-b2ea-acd57578d12c
This model is a fine-tuned version of Eurdem/Defne_llama3_2x8B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5818
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: 0.000206
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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: 50
- training_steps: 500
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0003 | 1 | 2.4653 |
1.8497 | 0.0142 | 50 | 1.8087 |
1.8626 | 0.0284 | 100 | 2.0875 |
1.7585 | 0.0426 | 150 | 1.7172 |
1.503 | 0.0568 | 200 | 2.5064 |
1.9315 | 0.0711 | 250 | 1.7083 |
1.6444 | 0.0853 | 300 | 2.0619 |
1.8748 | 0.0995 | 350 | 1.6251 |
1.8836 | 0.1137 | 400 | 1.6406 |
1.9295 | 0.1279 | 450 | 1.5842 |
2.1817 | 0.1421 | 500 | 1.5818 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1