Create val.sh

val.sh

@@ -0,0 +1,345 @@
+#!/bin/bash
+#SBATCH --job-name=ckpts
+#SBATCH --ntasks=1                   # number of MP tasks
+#SBATCH --nodes=1
+#SBATCH --cpus-per-task=40           # number of cores per tasks
+#SBATCH --hint=nomultithread         # we get physical cores not logical
+#SBATCH --time=20:00:00             # maximum execution time (HH:MM:SS)
+#SBATCH --output=%x-%j.out          # output file name
+#SBATCH --account=ajs@cpu
+#SBATCH --partition=cpu_p1
+
+set -x -e
+
+source $six_ALL_CCFRWORK/start-tr13f-6B3-ml-t0
+export HF_DATASETS_OFFLINE=1
+export TRANSFORMERS_OFFLINE=1
+conda activate muennighoffmodelconv
+
+CKPT_PATH=$six_ALL_CCFRSCRATCH/checkpoints/tr13f-6B3-ml-t0/checkpoints/tasky
+#CKPT_PATH=$six_ALL_CCFRSCRATCH/checkpoints/tr13f-6B3-ml-t0/checkpoints/p31lossseq
+
+CKPTS=(
+global_step250
+global_step500
+global_step750
+global_step1000
+global_step1250
+)
+EXAMPLE_CKPT=$six_ALL_CCFRSCRATCH/commun/experiments/muennighoff/bloomckpt/6b3t0/tr13f-6b3-ml-t0-lmtoks341b-t0toks13b-xp3capmixnewcodelonglossseq
+DUMP_PATH=$six_ALL_CCFRSCRATCH/commun/experiments/muennighoff/bloomckpt/6b3t0
+OUT_PREFIX=tasky_
+#OUT_PREFIX=p31lossseq
+
+TP=1
+
+### CONVERT ###
+
+
+for i in {0..6}; do
+CKPT=${CKPTS[$i]}
+echo "$i"
+echo "Running $CKPT"
+
+OUTPUTCKPT=$DUMP_PATH/"$OUT_PREFIX$CKPT"
+python $six_ALL_CCFRSCRATCH/commun/experiments/muennighoff/bloomckpt/transformers_clone/src/transformers/models/bloom/convert_bloom_original_checkpoint_to_pytorch.py --pytorch_dump_folder_path $OUTPUTCKPT --bloom_checkpoint_path $CKPT_PATH/$CKPT --pretraining_tp $TP --bloom_config_file $EXAMPLE_CKPT/config.json
+
+# Copy tokenizer.json etc
+cp -r $EXAMPLE_CKPT/*.json $OUTPUTCKPT/
+
+eval_script="./eval_$i.slurm"
+cat <<EOT > $eval_script
+#!/bin/bash
+#SBATCH --job-name=evaluate_t0
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=1          # crucial - only 1 task per dist per node!
+#SBATCH --cpus-per-task=8           # number of cores per tasks
+#SBATCH --hint=nomultithread         # we get physical cores not logical
+#SBATCH --gres=gpu:1                 # number of gpus
+#SBATCH --constraint=a100
+#SBATCH --time 5:00:00             # maximum execution time (HH:MM:SS)
+#SBATCH --output=%x-%j.out           # output file name
+#SBATCH --account=ajs@a100
+#SBATCH --array=0-168
+
+set -x -e
+
+source $six_ALL_CCFRWORK/start-py38-pt111
+conda activate thomas_t_zero_evaluation
+
+CHECKPOINT_PATH=$OUTPUTCKPT
+
+WORKDIR=/gpfswork/rech/six/commun/code/tr13f-6B3-ml-t0
+pushd "\$WORKDIR"
+OUTPUT_DIR="\$CHECKPOINT_PATH/evaluation"
+mkdir -p "\$OUTPUT_DIR"
+
+# Validation
+DATASETS_AND_CONFIGS_VAL=(
+head_qa,en,en,"multiple_choice_q_and_a_index_with_context_en",validation
+head_qa,en,en,"multiple_choice_q_and_a_en",validation
+head_qa,en,en,"multiple_choice_q_and_a_index_en",validation
+head_qa,en,en,"multiple_choice_a_and_q_with_context_en",validation
+head_qa,en,en,"multiple_choice_a_and_q_en",validation
+head_qa,es,en,"multiple_choice_q_and_a_index_with_context_en",validation
+head_qa,es,en,"multiple_choice_q_and_a_en",validation
+head_qa,es,en,"multiple_choice_q_and_a_index_en",validation
+head_qa,es,en,"multiple_choice_a_and_q_with_context_en",validation
+head_qa,es,en,"multiple_choice_a_and_q_en",validation
+climate_fever,None,None,"first_evidence_and_claim_itemization",test
+climate_fever,None,None,"claim_and_all_supporting_evidences",test
+climate_fever,None,None,"fifth_evidence_and_claim_itemization",test
+climate_fever,None,None,"third_evidence_claim_pair",test
+climate_fever,None,None,"second_evidence_and_claim_itemization",test
+codah,codah,None,"interrogative_instruction_after_sentence_and_choices",train
+codah,codah,None,"affirmative_instruction_before_sentence_and_choices",train
+codah,codah,None,"affirmative_instruction_after_sentence_and_choices",train
+aqua_rat,raw,None,"select_the_best_option",validation
+aqua_rat,raw,None,"answer_quiz",validation
+aqua_rat,raw,None,"Answer questions from options",validation
+commonsense_qa,None,None,"answer_given_question_without_options",validation
+commonsense_qa,None,None,"question_answering",validation
+commonsense_qa,None,None,"most_suitable_answer",validation
+amazon_reviews_multi,en,en,"prompt_title_to_star",validation
+amazon_reviews_multi,en,en,"prompt_review_to_star",validation
+amazon_reviews_multi,en,en,"prompt_body_title_to_star",validation
+amazon_reviews_multi,zh,en,"prompt_title_to_star",validation
+amazon_reviews_multi,zh,en,"prompt_review_to_star",validation
+amazon_reviews_multi,zh,en,"prompt_body_title_to_star",validation
+amazon_reviews_multi,fr,en,"prompt_title_to_star",validation
+amazon_reviews_multi,fr,en,"prompt_review_to_star",validation
+amazon_reviews_multi,fr,en,"prompt_body_title_to_star",validation
+amazon_reviews_multi,es,en,"prompt_title_to_star",validation
+amazon_reviews_multi,es,en,"prompt_review_to_star",validation
+amazon_reviews_multi,es,en,"prompt_body_title_to_star",validation
+art,None,None,"choose_hypothesis_options",validation
+art,None,None,"choose_hypothesis_believable",validation
+art,None,None,"choose_hypothesis",validation
+art,None,None,"choose_hypothesis_desc",validation
+art,None,None,"choose_hypothesis_likely",validation
+banking77,None,None,"help_page_topic",test
+banking77,None,None,"direct_to_which_department",test
+banking77,None,None,"rephrase_as_banking_term",test
+blbooksgenre,title_genre_classifiction,None,"multi-choice",train
+blbooksgenre,title_genre_classifiction,None,"premise_context_first",train
+blbooksgenre,title_genre_classifiction,None,"classify",train
+blimp,adjunct_island,None,"grammatical_between_1_2",train
+blimp,adjunct_island,None,"grammatical_between_A_B",train
+blimp,adjunct_island,None,"grammatical_which_one_1_2",train
+blimp,adjunct_island,None,"single_sentence_bad_yes_no",train
+blimp,adjunct_island,None,"single_sentence_good_yes_no",train
+conv_ai_3,None,None,"clarification_needed",validation
+conv_ai_3,None,None,"score_give_number",validation
+conv_ai_3,None,None,"ambiguous",validation
+conv_ai_3,None,None,"directly_answer",validation
+conv_ai_3,None,None,"score_how_much",validation
+craigslist_bargains,None,None,"good deal for seller no list price implicit",validation
+craigslist_bargains,None,None,"good deal for seller no list price",validation
+craigslist_bargains,None,None,"good deal for seller",validation
+craigslist_bargains,None,None,"best deal",validation
+ecthr_cases,alleged-violation-prediction,None,"implicit_advice_number",validation
+ecthr_cases,alleged-violation-prediction,None,"ecthr_alleged_articles_declaration_at_end",validation
+ecthr_cases,alleged-violation-prediction,None,"ecthr_alleged_articles_question_at_start",validation
+ecthr_cases,alleged-violation-prediction,None,"implicit_judgment_paragraph",validation
+ecthr_cases,alleged-violation-prediction,None,"confirm number of violated articles",validation
+emo,None,None,"persons_describe",validation
+emo,None,None,"final_message",validation
+emo,None,None,"what_emotion_do_you_think",validation
+emo,None,None,"emotional_state",validation
+emo,None,None,"dialogue_between",validation
+emotion,None,None,"choose_the_best_emotion_label",test
+emotion,None,None,"reply_with_emoation_label",test
+emotion,None,None,"answer_with_class_label",test
+emotion,None,None,"answer_question_with_emotion_label",test
+financial_phrasebank,sentences_allagree,None,"share_price_option",train
+financial_phrasebank,sentences_allagree,None,"sentiment",train
+financial_phrasebank,sentences_allagree,None,"word_comes_to_mind",train
+financial_phrasebank,sentences_allagree,None,"complementary_industries",train
+financial_phrasebank,sentences_allagree,None,"bullish_neutral_bearish",train
+glue,cola,None,"Make sense yes no",validation
+glue,cola,None,"is_this_correct",validation
+glue,cola,None,"editing",validation
+glue,cola,None,"Following sentence acceptable",validation
+glue,cola,None,"Previous sentence acceptable",validation
+glue,sst2,None,"positive negative after",validation
+glue,sst2,None,"review",validation
+glue,sst2,None,"said",validation
+glue,sst2,None,"following positive negative",validation
+glue,sst2,None,"happy or mad",validation
+health_fact,None,None,"claim_veracity_classification_after_reading_I_believe",validation
+health_fact,None,None,"claim_explanation_classification",validation
+health_fact,None,None,"claim_veracity_classification_tell_me",validation
+hlgd,None,None,"is_same_event_with_time_interrogative_related",validation
+hlgd,None,None,"is_same_event_interrogative_talk",validation
+hlgd,None,None,"is_same_event_with_time_interrogative_talk",validation
+hlgd,None,None,"is_same_event_refer",validation
+hlgd,None,None,"is_same_event_editor_asks",validation
+hyperpartisan_news_detection,byarticle,None,"consider_does_it_follow_a_hyperpartisan_argumentation",train
+hyperpartisan_news_detection,byarticle,None,"follows_hyperpartisan_argumentation",train
+hyperpartisan_news_detection,byarticle,None,"consume_with_caution",train
+hyperpartisan_news_detection,byarticle,None,"extreme_left_wing_or_right_wing",train
+hyperpartisan_news_detection,byarticle,None,"consider_it_exhibits_extreme_one_sidedness",train
+liar,None,None,"Given statement guess category",validation
+lince,sa_spaeng,None,"original poster expressed sentiment",validation
+lince,sa_spaeng,None,"sentiment trying to express",validation
+lince,sa_spaeng,None,"express sentiment",validation
+lince,sa_spaeng,None,"negation template",validation
+lince,sa_spaeng,None,"the author seem",validation
+math_qa,None,None,"choose_correct_og",test
+math_qa,None,None,"pick_the_correct",test
+math_qa,None,None,"first_choice_then_problem",test
+math_qa,None,None,"problem_set_type",test
+math_qa,None,None,"gre_problem",test
+movie_rationales,None,None,"Standard binary sentiment analysis",validation
+movie_rationales,None,None,"Evidences sentiment classification",validation
+movie_rationales,None,None,"Evidences + review",validation
+movie_rationales,None,None,"Generate evidences and sentiment",validation
+mwsc,None,None,"in-the-sentence-question-first",validation
+mwsc,None,None,"what-think",validation
+mwsc,None,None,"in-the-sentence",validation
+mwsc,None,None,"options-or",validation
+mwsc,None,None,"is-correct",validation
+poem_sentiment,None,None,"positive_or_negative_sentiment_variation_2",validation
+poem_sentiment,None,None,"question_answer_format",validation
+poem_sentiment,None,None,"guess_sentiment_without_options_variation_1",validation
+poem_sentiment,None,None,"positive_or_negative_sentiment_variation_1",validation
+poem_sentiment,None,None,"most_appropriate_sentiment",validation
+onestop_english,None,None,"esl_context",train
+onestop_english,None,None,"ara_context",train
+onestop_english,None,None,"determine_reading_level_from_the_first_three_sentences",train
+onestop_english,None,None,"esl_variation",train
+onestop_english,None,None,"assess",train
+pubmed_qa,pqa_labeled,None,"Long Answer to Final Decision",train
+pubmed_qa,pqa_labeled,None,"Question Answering (Short)",train
+riddle_sense,None,None,"most_suitable_answer",validation
+riddle_sense,None,None,"answer_given_question_without_options",validation
+riddle_sense,None,None,"question_to_answer_index",validation
+riddle_sense,None,None,"question_answering",validation
+scicite,None,None,"Classify intent w/section (select choice)",validation
+scicite,None,None,"Classify intent (choices first)",validation
+scicite,None,None,"Classify intent (select choice)",validation
+scicite,None,None,"Classify intent",validation
+scicite,None,None,"can_describe",validation
+selqa,answer_selection_analysis,None,"is-he-talking-about",validation
+selqa,answer_selection_analysis,None,"would-make-sense-qu-rand",validation
+selqa,answer_selection_analysis,None,"make-sense-rand",validation
+selqa,answer_selection_analysis,None,"which-answer-1st-vs-random",validation
+snips_built_in_intents,None,None,"voice_intent",train
+snips_built_in_intents,None,None,"categorize_query",train
+snips_built_in_intents,None,None,"intent_query",train
+snips_built_in_intents,None,None,"categorize_query_brief",train
+snips_built_in_intents,None,None,"query_intent",train
+)
+
+DATASET_AND_CONFIG="\${DATASETS_AND_CONFIGS_VAL[\$SLURM_ARRAY_TASK_ID]}"
+echo "\$ARGUMENT"
+
+# Run T0 evaluation
+# For PrefixLM add --prefixlm
+IFS=',' read dataset_name dataset_config_name template_config_name template_name split <<< "\${DATASET_AND_CONFIG}"
+python t-zero/evaluation/run_eval.py \
+        --dataset_name "\$dataset_name" \
+        --dataset_config_name "\$dataset_config_name" \
+        --template_config_name "\$template_config_name" \
+        --template_name "\$template_name" \
+        --split "\$split" \
+        --model_name_or_path "\$CHECKPOINT_PATH" \
+        --output_dir "\$OUTPUT_DIR" \
+        --per_device_eval_batch_size 4 \
+        --max_length 2048 \
+        --dtype float16
+EOT
+
+sbatch $eval_script
+
+
+lm_eval_script="./lm_eval_$i.slurm"
+cat <<EOT > $lm_eval_script
+#!/bin/bash
+#SBATCH --job-name=lmeval
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=1          # crucial - only 1 task per dist per node!
+#SBATCH --cpus-per-task=8           # number of cores per tasks
+#SBATCH --hint=nomultithread         # we get physical cores not logical
+#SBATCH --gres=gpu:1                 # number of gpus
+#SBATCH --constraint=a100
+#SBATCH --time 20:00:00             # maximum execution time (HH:MM:SS)
+#SBATCH --output=%x-%j.out           # output file name
+#SBATCH --account=ajs@a100
+#SBATCH --array=0-12
+
+set -x -e
+
+source $six_ALL_CCFRWORK/start-tr13f-6B3-ml-t0
+conda activate muennighofflmevalgen
+
+echo "START TIME: $(date)"
+
+# defining the right environment variables
+export TRANSFORMERS_CACHE=$six_ALL_CCFRWORK/models
+export HF_DATASETS_CACHE=$six_ALL_CCFRWORK/datasets
+export HF_MODULES_CACHE=$six_ALL_CCFRWORK/modules
+export HF_METRICS_CACHE=$six_ALL_CCFRWORK/metrics
+export HF_DATASETS_OFFLINE=1
+export TRANSFORMERS_OFFLINE=1
+export TOKENIZERS_PARALLELISM=false
+
+# Converted transformer checkpoint
+MODEL_CKPT=$OUTPUTCKPT
+
+cd /gpfsscratch/rech/six/commun/experiments/muennighoff/lm-evaluation-harness
+
+
+DATASETS_AND_CONFIGS=(
+wmt14_fr_en,fr-en,"version-en-fr-target"
+wmt14_fr_en,fr-en,"a_good_translation-en-fr-target"
+wmt14_fr_en,fr-en,"a_good_translation-en-fr-source+target"
+wmt14_fr_en,fr-en,"xglm-en-fr-target"
+wmt14_fr_en,fr-en,"gpt3-en-fr"
+wmt14_fr_en,fr-en,"version-fr-en-target"
+wmt14_fr_en,fr-en,"a_good_translation-fr-en-target"
+wmt14_fr_en,fr-en,"a_good_translation-fr-en-source+target"
+wmt14_fr_en,fr-en,"xglm-fr-en-target"
+wmt14_fr_en,fr-en,"gpt3-fr-en"
+wmt14_hi_en,hi-en,"version-en-hi-target"
+wmt14_hi_en,hi-en,"a_good_translation-en-hi-target"
+wmt14_hi_en,hi-en,"a_good_translation-en-hi-source+target"
+wmt14_hi_en,hi-en,"xglm-en-hi-target"
+wmt14_hi_en,hi-en,"gpt-3-en-hi-target"
+wmt14_hi_en,hi-en,"version-hi-en-target"
+wmt14_hi_en,hi-en,"a_good_translation-hi-en-target"
+wmt14_hi_en,hi-en,"a_good_translation-hi-en-source+target"
+wmt14_hi_en,hi-en,"xglm-hi-en-target"
+wmt14_hi_en,hi-en,"gpt-3-hi-en-target"
+mlsum_es,"es","layman_summ_es"
+mlsum_es,"es","palm_prompt"
+mlsum_es,"es","summarise_this_in_es_few_sentences"
+)
+
+DATASET_AND_CONFIG="\${DATASETS_AND_CONFIGS[\$SLURM_ARRAY_TASK_ID]}"
+echo "\$ARGUMENT"
+
+IFS=',' read dataset_name lang template_name <<< "\${DATASET_AND_CONFIG}"
+
+# Use this fork of lm-eval: https://github.com/bigscience-workshop/lm-evaluation-harness/pull/109
+python main.py \
+    --model_api_name 'hf-causal' \
+    --model_args "pretrained=\$MODEL_CKPT,use_accelerate=True,tokenizer=\$MODEL_CKPT,dtype=float16" \
+    --device cuda \
+    --batch_size 16 \
+    --no_tracking \
+    --task_name "\$dataset_name" \
+    --template_names "\$template_name" \
+    --bootstrap_iters 10 \
+    --limit 3000
+
+mkdir -p "$OUTPUTCKPT/evaluation/\$dataset_name"
+mv "outputs/*$CKPT*\$dataset_name*" "$OUTPUTCKPT/evaluation/\$dataset_name/"
+
+echo "END TIME: $(date)"
+EOT
+
+sbatch $lm_eval_script
+
+
+done