See axolotl config

axolotl version: 0.4.1

adapter: lora
base_model: unsloth/Meta-Llama-3.1-8B
bf16: auto
chat_template: llama3
dataset_prepared_path: null
dataset_processes: 12
datasets:
- data_files:
  - /workspace/axolotl/data/356953bd-f938-4862-a3a5-21d61fce48ce.json
  ds_type: json
  path: /workspace/axolotl/data/356953bd-f938-4862-a3a5-21d61fce48ce.json
  type:
    field_input: assistant
    field_instruction: reasoning
    field_output: user
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 512
eval_table_size: null
evals_per_epoch: 2
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: ncbateman/tuning-miner-testbed-356953bd-f938-4862-a3a5-21d61fce48ce
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: true
local_rank: null
logging_steps: 1
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: cosine
micro_batch_size: 4
mlflow_experiment_name: https://5a301a635a9d0ac3cb7fcc3bf373c3c3.r2.cloudflarestorage.com/tuning/starsnatched/thinker_train_data.json?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=d49fdd0cc9750a097b58ba35b2d9fbed%2F20241025%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20241025T131146Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=9b6d0bb0018a1eb8b79fe4ae3540b07fc752316286d4c60b17353da267d7383a
model_type: LlamaForCausalLM
num_epochs: 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: 20
save_strategy: steps
sequence_len: 4096
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
val_set_size: 0.05
wandb_entity: breakfasthut
wandb_mode: online
wandb_project: tuning-miner
wandb_run: miner
wandb_runid: 356953bd-f938-4862-a3a5-21d61fce48ce
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null

tuning-miner-testbed-356953bd-f938-4862-a3a5-21d61fce48ce

This model is a fine-tuned version of unsloth/Meta-Llama-3.1-8B on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.0643

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: 0.0001
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• total_eval_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 50
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss
1.5069	0.0090	1	1.4913
0.8008	0.5034	56	0.8206
0.8149	1.0067	112	0.7789
0.7494	1.5101	168	0.7758
0.6004	2.0135	224	0.7671
0.5752	2.5169	280	0.8159
0.3785	3.0202	336	0.8351
0.4173	3.5236	392	0.9273
0.3035	4.0270	448	0.9567
0.2218	4.5303	504	1.0643

Framework versions

• PEFT 0.13.2
• Transformers 4.45.2
• Pytorch 2.3.1+cu121
• Datasets 3.0.1
• Tokenizers 0.20.1