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nttx/
8c6dfe77-4b4e-4687-a4bc-b4b53b3a5dae

Name: 8c6dfe77-4b4e-4687-a4bc-b4b53b3a5dae
Rating: 2.5 (9 reviews)

generated_from_trainer

unsloth/Llama-3.2-3B

adapter

llama3.2

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: unsloth/Llama-3.2-3B
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
  - 70a7479d47363ab3_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/70a7479d47363ab3_train_data.json
  type:
    field_input: alpaca_prompt
    field_instruction: instruction
    field_output: response
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: 2
eval_batch_size: 8
eval_max_new_tokens: 128
eval_steps: 500
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: nttx/8c6dfe77-4b4e-4687-a4bc-b4b53b3a5dae
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0003
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 500
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_memory:
  0: 75GB
max_steps: 5000
micro_batch_size: 8
mlflow_experiment_name: /tmp/70a7479d47363ab3_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 100
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.95
  adam_epsilon: 1e-5
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: 500
saves_per_epoch: null
sequence_len: 1024
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: 216a93cc-a197-4cb5-90dc-eb062c873f63
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 216a93cc-a197-4cb5-90dc-eb062c873f63
warmup_steps: 100
weight_decay: 0.0
xformers_attention: null

8c6dfe77-4b4e-4687-a4bc-b4b53b3a5dae

This model is a fine-tuned version of unsloth/Llama-3.2-3B on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0854

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: 0.0003
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0005	1	1.8803
1.6753	0.2683	500	1.8831
1.6268	0.5366	1000	1.7455
1.5469	0.8049	1500	1.6103
1.3544	1.0732	2000	1.4402
1.0164	1.3416	2500	1.3515
0.9548	1.6099	3000	1.2334
0.8664	1.8782	3500	1.1175
0.6149	2.1465	4000	1.1138
0.4393	2.4148	4500	1.0886
0.4256	2.6831	5000	1.0854

Framework versions

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