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0.4.11adapter: lora
2base_model: unsloth/mistral-7b-v0.3
3bf16: true
4chat_template: llama3
5dataset_prepared_path: null
6datasets:
7- data_files:
8 - 22c390fa2fd3454c_train_data.json
9 ds_type: json
10 format: custom
11 path: /workspace/input_data/22c390fa2fd3454c_train_data.json
12 type:
13 field_input: Input
14 field_instruction: Instruction
15 field_output: Output
16 format: '{instruction} {input}'
17 no_input_format: '{instruction}'
18 system_format: '{system}'
19 system_prompt: ''
20debug: null
21device_map:
22 ? ''
23 : 0,1,2,3,4,5,6,7
24early_stopping_patience: 2
25eval_max_new_tokens: 128
26eval_steps: 100
27eval_table_size: null
28flash_attention: true
29gradient_accumulation_steps: 8
30gradient_checkpointing: true
31group_by_length: false
32hub_model_id: Alphatao/6c34f98c-7e4f-4d22-befc-acd1929938e2
33hub_repo: null
34hub_strategy: null
35hub_token: null
36learning_rate: 0.0002
37load_best_model_at_end: true
38load_in_4bit: false
39load_in_8bit: false
40local_rank: null
41logging_steps: 1
42lora_alpha: 128
43lora_dropout: 0.1
44lora_fan_in_fan_out: null
45lora_model_dir: null
46lora_r: 64
47lora_target_linear: true
48lora_target_modules:
49- q_proj
50- k_proj
51- v_proj
52- o_proj
53lr_scheduler: cosine
54max_grad_norm: 1.0
55max_steps: 966
56micro_batch_size: 4
57mlflow_experiment_name: /tmp/22c390fa2fd3454c_train_data.json
58model_type: AutoModelForCausalLM
59num_epochs: 2
60optimizer: adamw_bnb_8bit
61output_dir: miner_id_24
62pad_to_sequence_len: true
63resume_from_checkpoint: null
64s2_attention: null
65sample_packing: false
66save_steps: 100
67sequence_len: 2048
68strict: false
69tf32: true
70tokenizer_type: AutoTokenizer
71train_on_inputs: false
72trust_remote_code: true
73val_set_size: 0.04
74wandb_entity: null
75wandb_mode: online
76wandb_name: 6eece874-15cc-4a69-9d22-190de373b23f
77wandb_project: Gradients-On-Demand
78wandb_run: your_name
79wandb_runid: 6eece874-15cc-4a69-9d22-190de373b23f
80warmup_steps: 10
81weight_decay: 0.0
82xformers_attention: null
83| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.4524 | 0.0010 | 1 | 0.6885 |
| 4.1768 | 0.0983 | 100 | 0.5170 |
| 3.8307 | 0.1966 | 200 | 0.4812 |
| 3.6582 | 0.2948 | 300 | 0.4591 |
| 4.3532 | 0.3931 | 400 | 0.4399 |
| 3.6323 | 0.4914 | 500 | 0.4239 |
| 3.8378 | 0.5897 | 600 | 0.4111 |
| 2.7167 | 0.6880 | 700 | 0.4002 |
| 3.297 | 0.7862 | 800 | 0.3930 |
| 3.0928 | 0.8845 | 900 | 0.3900 |