dada22231/5648c292-f19f-40a7-b24f-79454923d7e5

See axolotl config

axolotl version: 0.10.0.dev0

adapter: lora
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
bf16: true
chat_template: llama3
dataloader_num_workers: 8
dataloader_pin_memory: true
dataloader_prefetch_factor: 2
dataset_prepared_path: null
datasets:
- data_files:
  - test_dataset.json
  ds_type: json
  format: custom
  path: /workspace/input_data/
  type:
    field_input: input
    field_instruction: instruction
    field_output: output
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
ddp_broadcast_buffers: false
ddp_bucket_cap_mb: 25
ddp_timeout: 7200
debug: null
deepspeed: null
eval_batch_size: 16
eval_max_new_tokens: 128
eval_sample_packing: false
eval_table_size: null
evals_per_epoch: 0
flash_attention: true
flash_attn_cross_entropy: true
flash_attn_rms_norm: true
fp16: false
fsdp: null
fsdp_config: null
gpu_memory_limit: null
gradient_accumulation_steps: 2
gradient_checkpointing: false
gradient_checkpointing_kwargs:
  use_reentrant: false
group_by_length: false
hub_model_id: dada22231/test-model-2b61e779
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0005
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_modules_to_save:
- embed_tokens
- lm_head
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_memory: null
micro_batch_size: 32
mlflow_experiment_name: /tmp/tmp7q_5jixf/test_dataset.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_torch_fused
output_dir: ./outputs
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: true
save_only_model: true
save_safetensors: true
saves_per_epoch: 1
sequence_len: 4096
special_tokens: null
strict: false
tf32: true
tokenizer_type: AutoTokenizer
torch_compile: false
torch_compile_backend: inductor
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.01
wandb_entity: null
wandb_mode: online
wandb_name: 2b61e779-25a5-40d4-aded-c853d5d2febb
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 2b61e779-25a5-40d4-aded-c853d5d2febb
warmup_ratio: 0.03
weight_decay: 0.01
xformers_attention: null

test-model-2b61e779

This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on an unknown 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: 0.0005
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• 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_ratio: 0.03
• num_epochs: 1.0

Training results

Framework versions

• PEFT 0.15.2
• Transformers 4.52.3
• Pytorch 2.5.1+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1