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0.10.0.dev01adapter: lora
2base_model: NousResearch/Hermes-3-Llama-3.1-8B
3bf16: true
4datasets:
5- data_files:
6 - f7961f5a6bb36a2f_train_data.json
7 ds_type: json
8 format: custom
9 path: /workspace/input_data/
10 type:
11 field_instruction: instruct
12 field_output: output
13 format: '{instruction}'
14 no_input_format: '{instruction}'
15 system_format: '{system}'
16 system_prompt: ''
17eval_max_new_tokens: 128
18evals_per_epoch: 4
19flash_attention: false
20fp16: false
21gradient_accumulation_steps: 1
22gradient_checkpointing: true
23group_by_length: true
24hub_model_id: segopecelus/da319ce3-fc81-4de7-9c7d-13f77a773fba
25learning_rate: 0.0002
26load_in_4bit: false
27logging_steps: 10
28lora_alpha: 16
29lora_dropout: 0.05
30lora_fan_in_fan_out: false
31lora_r: 8
32lora_target_linear: true
33lr_scheduler: cosine
34max_steps: 1170
35micro_batch_size: 24
36mlflow_experiment_name: /tmp/f7961f5a6bb36a2f_train_data.json
37output_dir: miner_id_24
38rl: null
39sample_packing: true
40save_steps: 0
41sequence_len: 2048
42tf32: true
43tokenizer_type: AutoTokenizer
44train_on_inputs: true
45trl: null
46trust_remote_code: true
47wandb_name: c0b5b71f-e0e5-4165-84b6-df5583a37da4
48wandb_project: Gradients-On-Demand
49wandb_run: apriasmoro
50wandb_runid: c0b5b71f-e0e5-4165-84b6-df5583a37da4
51warmup_steps: 100
52weight_decay: 0.01
53