You can deploy this model and start earning money today!

rayonlabs/
benchmark-90cda45e-2a5b-4988-8ee4-a159b5a34510-tourn_da7517a5dac130db_20250807-5DjoSN4t

Name: benchmark-90cda45e-2a5b-4988-8ee4-a159b5a34510-tourn_da7517a5dac130db_20250807-5DjoSN4t
Availability: InStock

peft

safetensors

llama

generated_from_trainer

unsloth/llama-3-8b-Instruct

adapter

Views

No views yet

See axolotl config

axolotl version: 0.11.0.dev0

yaml

adapter: lora
base_model: unsloth/llama-3-8b-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 4302bdd9-e624-47b7-8c1d-352ac43191b4_train_data.json
  ds_type: json
  format: custom
  path: /workspace/axolotl/data
  type:
    field_instruction: instruct
    field_output: output
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: false
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_steps: 10
micro_batch_size: 2
mlflow_experiment_name: /workspace/axolotl/data/4302bdd9-e624-47b7-8c1d-352ac43191b4_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: /app/checkpoints/4302bdd9-e624-47b7-8c1d-352ac43191b4/benchmark-90cda45e-2a5b-4988-8ee4-a159b5a34510-tourn_da7517a5dac130db_20250807-5DjoSN4t
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
sequence_len: 512
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: offline
wandb_name: 4302bdd9-e624-47b7-8c1d-352ac43191b4_benchmark-90cda45e-2a5b-4988-8ee4-a159b5a34510-tourn_da7517a5dac130db_20250807-5DjoSN4t
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 4302bdd9-e624-47b7-8c1d-352ac43191b4_benchmark-90cda45e-2a5b-4988-8ee4-a159b5a34510-tourn_da7517a5dac130db_20250807-5DjoSN4t
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

app/checkpoints/4302bdd9-e624-47b7-8c1d-352ac43191b4/benchmark-90cda45e-2a5b-4988-8ee4-a159b5a34510-tourn_da7517a5dac130db_20250807-5DjoSN4t

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.6341

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
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: 10
training_steps: 10

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0	0	1.9933
1.02	0.0002	3	1.9893
1.1494	0.0004	6	1.9295
1.3007	0.0006	9	1.6341

Framework versions

PEFT 0.15.2
Transformers 4.53.1
Pytorch 2.5.1+cu124
Datasets 3.6.0
Tokenizers 0.21.2

rayonlabs/benchmark-90cda45e-2a5b-4988-8ee4-a159b5a34510-tourn_da7517a5dac130db_20250807-5DjoSN4t

app/checkpoints/4302bdd9-e624-47b7-8c1d-352ac43191b4/benchmark-90cda45e-2a5b-4988-8ee4-a159b5a34510-tourn_da7517a5dac130db_20250807-5DjoSN4t

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

rayonlabs/
benchmark-90cda45e-2a5b-4988-8ee4-a159b5a34510-tourn_da7517a5dac130db_20250807-5DjoSN4t