mayyteee/21ace486-7246-492d-9bad-f57281c4ba33

See axolotl config

axolotl version: 0.4.1

adapter: lora
auto_find_batch_size: false
base_model: unsloth/Qwen2-1.5B-Instruct
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
  - b734323335b87c24_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/b734323335b87c24_train_data.json
  type:
    field_instruction: question
    field_output: answer
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 
early_stopping_threshold: 1.0e-07
eval_max_new_tokens: 128
eval_steps: 
eval_strategy: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 6
gradient_checkpointing: false
group_by_length: false
hub_model_id: 
hub_repo: null
hub_strategy: all_checkpoints
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 
lora_alpha: 64
lora_dropout: 0.15
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1
max_steps: 50
micro_batch_size: 12
mlflow_experiment_name: /tmp/b734323335b87c24_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 200
optimizer: adamw_torch_fused
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 
save_total_limit: 10
saves_per_epoch: 0
sequence_len: 1024
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
use_rslora: true
val_set_size: 0.0
wandb_entity: null
wandb_mode: disabled
wandb_name: f8eadb09-2bd0-4365-aae9-b645b7e8c683
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: f8eadb09-2bd0-4365-aae9-b645b7e8c683
warmup_steps: 100
weight_decay: 0.01
xformers_attention: null

miner_id_24

This model is a fine-tuned version of unsloth/Qwen2-1.5B-Instruct on the None 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: 12
• eval_batch_size: 12
• seed: 42
• gradient_accumulation_steps: 6
• total_train_batch_size: 72
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 100
• training_steps: 50

Training results

Framework versions

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