You can deploy this model and start earning money today!

aleegis/
5b5edef6-20b1-4da5-9864-c364f4ac05d5

Name: 5b5edef6-20b1-4da5-9864-c364f4ac05d5
Availability: InStock

generated_from_trainer

unsloth/SmolLM-1.7B

adapter

apache-2.0

Views

No views yet

See axolotl config

axolotl version: 0.10.0.dev0

yaml

adapter: lora
base_model: unsloth/SmolLM-1.7B
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
  - da6901d849324b9e_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/
  type:
    field_input: input
    field_instruction: instruct
    field_output: output
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_steps: null
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: false
group_by_length: false
hub_model_id: aleegis/5b5edef6-20b1-4da5-9864-c364f4ac05d5
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: null
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: constant
max_grad_norm: 1
max_steps: 800
micro_batch_size: 4
mlflow_experiment_name: /tmp/da6901d849324b9e_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 15
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: null
save_total_limit: 10
saves_per_epoch: 0
sequence_len: 2048
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.0
wandb_entity: null
wandb_mode: online
wandb_name: 77cb7152-00ec-4da2-a927-6632e7e5f5b5
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 77cb7152-00ec-4da2-a927-6632e7e5f5b5
warmup_steps: 80
weight_decay: 0
xformers_attention: null

5b5edef6-20b1-4da5-9864-c364f4ac05d5

This model is a fine-tuned version of unsloth/SmolLM-1.7B 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: 0.0002
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
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: constant
lr_scheduler_warmup_steps: 80
training_steps: 800

Training results

Framework versions

PEFT 0.15.2
Transformers 4.51.3
Pytorch 2.5.1+cu124
Datasets 3.5.1
Tokenizers 0.21.1