cjwbw/lorahub 🔢📝 → 🖼️
About
Efficient Cross-Task Generalization via Dynamic LoRA Composition
Example Output
Output
Performance Metrics
146.18s
Prediction Time
150.51s
Total Time
All Input Parameters
{
"example_inputs": "Infer the date from context. Q: Today, 8/3/1997, is a day that we will never forget. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 03/27/1998 (B) 09/02/1997 (C) 07/27/1997 (D) 06/29/1997 (E) 07/27/1973 (F) 12/27/1997 A:\nInfer the date from context. Q: May 6, 1992 is like yesterday to Jane, but that is actually ten years ago. What is the date tomorrow in MM/DD/YYYY? Options: (A) 04/16/2002 (B) 04/07/2003 (C) 05/07/2036 (D) 05/28/2002 (E) 05/07/2002 A:\nInfer the date from context. Q: Today is the second day of the third month of 1966. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 02/26/1966 (B) 01/13/1966 (C) 02/02/1966 (D) 10/23/1966 (E) 02/23/1968 (F) 02/23/1966 A:",
"example_outputs": "(C)\n(E)\n(F)",
"max_inference_step": 40,
"num_random_lora_modules": 20
}
Input Parameters
- seed
- Random seed. Leave blank to randomize the seed.
- example_inputs
- List of input examples, one Line one input.
- example_outputs
- List of output examples, one Line one output.
- max_inference_step
- Maximum iteration steps to maximise LoRA module composition. We suggest setting it to 40 steps if 20 modules were chosen, with more steps typically needed for more modules.
- lora_modules_specified
- Specify LoRA modules for the composition, options are from https://huggingface.co/models?search=lorahub, separated modules with comma, e.g. 'lorahub/flan_t5_large-quarel_logic_test, lorahub/flan_t5_large-coqa'
- num_random_lora_modules
- Set number of LoRA modules to use. Ignored if specified modules above.
Output Schema
Output
Example Execution Logs
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lorahub/flan_t5_large-wiqa_what_might_be_the_last_step_of_the_process ... 70%|███████ | 14/20 [00:16<00:08, 1.39s/it] Downloading (…)/adapter_config.json: 0%| | 0.00/411 [00:00<?, ?B/s][A Downloading (…)/adapter_config.json: 100%|██████████| 411/411 [00:00<00:00, 1.23MB/s] Downloading adapter_model.bin: 0%| | 0.00/19.0M [00:00<?, ?B/s][A Downloading adapter_model.bin: 55%|█████▌ | 10.5M/19.0M [00:00<00:00, 59.9MB/s][A Downloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 58.5MB/s][A Downloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 56.9MB/s] > Loading lorahub/flan_t5_large-super_glue_cb ... 75%|███████▌ | 15/20 [00:17<00:06, 1.34s/it] Downloading (…)/adapter_config.json: 0%| | 0.00/411 [00:00<?, ?B/s][A Downloading (…)/adapter_config.json: 100%|██████████| 411/411 [00:00<00:00, 1.33MB/s] Downloading adapter_model.bin: 0%| | 0.00/19.0M [00:00<?, ?B/s][A Downloading adapter_model.bin: 55%|█████▌ | 10.5M/19.0M [00:00<00:00, 89.3MB/s][A Downloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 97.2MB/s] > Loading lorahub/flan_t5_large-quarel_heres_a_story ... 80%|████████ | 16/20 [00:18<00:05, 1.28s/it] Downloading (…)/adapter_config.json: 0%| | 0.00/411 [00:00<?, ?B/s][A Downloading (…)/adapter_config.json: 100%|██████████| 411/411 [00:00<00:00, 1.40MB/s] Downloading adapter_model.bin: 0%| | 0.00/19.0M [00:00<?, ?B/s][A Downloading adapter_model.bin: 55%|█████▌ | 10.5M/19.0M [00:00<00:00, 79.3MB/s][A Downloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 62.5MB/s][A Downloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 62.5MB/s] > Loading lorahub/flan_t5_large-race_middle_Is_this_the_right_answer ... 85%|████████▌ | 17/20 [00:20<00:03, 1.31s/it] Downloading (…)/adapter_config.json: 0%| | 0.00/411 [00:00<?, ?B/s][A Downloading (…)/adapter_config.json: 100%|██████████| 411/411 [00:00<00:00, 1.26MB/s] Downloading adapter_model.bin: 0%| | 0.00/19.0M [00:00<?, ?B/s][A Downloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 145MB/s][A Downloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 133MB/s] > Loading lorahub/flan_t5_large-adversarial_qa_dbidaf_answer_the_following_q ... 90%|█████████ | 18/20 [00:21<00:02, 1.23s/it] Downloading (…)/adapter_config.json: 0%| | 0.00/411 [00:00<?, ?B/s][A Downloading (…)/adapter_config.json: 100%|██████████| 411/411 [00:00<00:00, 655kB/s] Downloading adapter_model.bin: 0%| | 0.00/19.0M [00:00<?, ?B/s][A Downloading adapter_model.bin: 55%|█████▌ | 10.5M/19.0M [00:00<00:00, 59.2MB/s][A Downloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 73.8MB/s] > Loading lorahub/flan_t5_large-race_middle_Select_the_best_answer_generate_span_ ... 95%|█████████▌| 19/20 [00:22<00:01, 1.23s/it] Downloading (…)/adapter_config.json: 0%| | 0.00/411 [00:00<?, ?B/s][A Downloading (…)/adapter_config.json: 100%|██████████| 411/411 [00:00<00:00, 1.31MB/s] Downloading adapter_model.bin: 0%| | 0.00/19.0M [00:00<?, ?B/s][A Downloading adapter_model.bin: 55%|█████▌ | 10.5M/19.0M [00:00<00:00, 93.8MB/s][A Downloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 107MB/s] 100%|██████████| 20/20 [00:23<00:00, 1.12s/it] 100%|██████████| 20/20 [00:23<00:00, 1.17s/it] Running tokenizer on dataset: 0%| | 0/3 [00:00<?, ? examples/s] Running tokenizer on dataset: 100%|██████████| 3/3 [00:00<00:00, 112.81 examples/s] > Begin to perform gradient-free optimization ... Launching 1 jobs with new suggestions Updating fitness with value 0.19794374704360962 39 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.19664074103037515 38 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.20196577151616416 37 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18949530760447184 36 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18646785974502564 35 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18851580699284873 34 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.17956692457199097 33 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18219556013743082 32 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18811706304550171 31 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18308404684066773 30 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.15466183026631675 29 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.13169783075650532 28 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.11195437947909037 27 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.14315053780873618 26 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.09870247999827067 25 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.09308040221532185 24 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08350652158260345 23 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.1701445213953654 22 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08785513858000438 21 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18224913199742637 20 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.887497984568278 19 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.20113089762185843 18 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08463106314341227 17 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.179056189929146 16 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.07683334509531657 15 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.17642755043471342 14 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.06571920676354828 13 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.0742276668098602 12 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.05183583021748306 11 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.12994661993059228 10 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08364694323973731 9 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08870862409630972 8 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08821432639038829 7 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.05691506158264563 6 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.05956370060788695 5 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.13098620907509662 4 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.06969356769947482 3 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.09138107303580391 2 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.061673278693635536 1 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.045564029637715844 0 remaining budget and 0 running jobs The recommended weight set for the LoRA modules is: 0.4984: lorahub/flan_t5_large-wmt16_translate_ro-en -0.2598: lorahub/flan_t5_large-anli_r2 0.4774: lorahub/flan_t5_large-gem_e2e_nlg 1.0626: lorahub/flan_t5_large-quartz_read_passage_below_choose 0.0428: lorahub/flan_t5_large-wiki_qa_Decide_good_answer 0.4685: lorahub/flan_t5_large-race_high_Select_the_best_answer_no_instructions_ -0.0285: lorahub/flan_t5_large-app_reviews_convert_to_rating -0.0458: lorahub/flan_t5_large-glue_mnli -0.0571: lorahub/flan_t5_large-sentiment140 0.5707: lorahub/flan_t5_large-quail_context_description_question_answer_id 0.5296: lorahub/flan_t5_large-snli 0.3255: lorahub/flan_t5_large-dbpedia_14_pick_one_category_for_the_following_text -0.0600: lorahub/flan_t5_large-quac 0.5097: lorahub/flan_t5_large-quoref_What_Is_The_Answer 0.5041: lorahub/flan_t5_large-wiqa_what_might_be_the_last_step_of_the_process 0.5070: lorahub/flan_t5_large-super_glue_cb -0.1103: lorahub/flan_t5_large-quarel_heres_a_story -0.0032: lorahub/flan_t5_large-race_middle_Is_this_the_right_answer -0.0723: lorahub/flan_t5_large-adversarial_qa_dbidaf_answer_the_following_q 0.0988: lorahub/flan_t5_large-race_middle_Select_the_best_answer_generate_span_
Version Details
- Version ID
02a0166b0b1deeec3e794ced2dc6c670592302e158c9ec51b676279afd0e6238- Version Created
- August 3, 2023