init
Browse files
experiments/huggingface_ops.py
CHANGED
@@ -3,7 +3,7 @@ from pprint import pprint
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api = HfApi()
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models = api.list_models(filter=ModelFilter(author='vocabtrimmer'))
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models_filtered = [i.modelId for i in models if '
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pprint(sorted(models_filtered))
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# models = api.list_models(filter=ModelFilter(author='tweettemposhift'))
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# models_filtered = [i.modelId for i in models if 'topic-' in i.modelId]
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api = HfApi()
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models = api.list_models(filter=ModelFilter(author='vocabtrimmer'))
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models_filtered = [i.modelId for i in models if 'cardiffnlp/twitter-roberta-base-jun2020' in i.modelId]
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pprint(sorted(models_filtered))
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# models = api.list_models(filter=ModelFilter(author='tweettemposhift'))
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# models_filtered = [i.modelId for i in models if 'topic-' in i.modelId]
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experiments/main.sh
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@@ -10,12 +10,6 @@ MODEL="cardiffnlp/twitter-roberta-base-2021-124m"
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MODEL="cardiffnlp/twitter-roberta-base-2022-154m"
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MODEL="cardiffnlp/twitter-roberta-large-2022-154m"
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# ABLATION (TimeLMs)
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## Topic & NER
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MODEL="cardiffnlp/twitter-roberta-base-jun2020"
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MODEL="cardiffnlp/twitter-roberta-base-sep2021"
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## NERD
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MODEL="cardiffnlp/twitter-roberta-base-jun2021"
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# SENTIMENT
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python model_finetuning_sentiment.py -m "${MODEL}" -d "sentiment_small_temporal"
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@@ -78,34 +72,49 @@ python model_finetuning_topic.py -m "${MODEL}" -d "topic_random2_seed2"
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python model_finetuning_topic.py -m "${MODEL}" -d "topic_random3_seed2"
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download () {
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git clone "https://huggingface.co/tweettemposhift/ner-${1}-${
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mkdir "ckpt/ner-${1}-${
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mv "ner-${1}-${
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mv "ckpt/ner-${1}-${
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}
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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download "
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python model_finetuning_ner.py -m "${
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MODEL="cardiffnlp/twitter-roberta-base-2022-154m"
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MODEL="cardiffnlp/twitter-roberta-large-2022-154m"
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# SENTIMENT
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python model_finetuning_sentiment.py -m "${MODEL}" -d "sentiment_small_temporal"
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python model_finetuning_topic.py -m "${MODEL}" -d "topic_random3_seed2"
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download () {
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git clone "https://huggingface.co/tweettemposhift/ner-${1}-${2##*/}"
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mkdir "ckpt/ner-${1}-${2##*/}"
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mv "ner-${1}-${2##*/}" "ckpt/ner-${1}-${2##*/}/"
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mv "ckpt/ner-${1}-${2##*/}/ner-${1}-${2##*/}" "ckpt/ner-${1}-${2##*/}/best_model"
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}
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fix () {
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download "ner_temporal" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_temporal" --skip-train
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download "ner_random0_seed0" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random0_seed0" --skip-train
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download "ner_random1_seed0" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random1_seed0" --skip-train
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download "ner_random2_seed0" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random2_seed0" --skip-train
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download "ner_random3_seed0" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random3_seed0" --skip-train
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download "ner_random0_seed1" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random0_seed1" --skip-train
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download "ner_random1_seed1" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random1_seed1" --skip-train
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download "ner_random2_seed1" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random2_seed1" --skip-train
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download "ner_random3_seed1" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random3_seed1" --skip-train
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download "ner_random0_seed2" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random0_seed2" --skip-train
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download "ner_random1_seed2" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random1_seed2" --skip-train
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download "ner_random2_seed2" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random2_seed2" --skip-train
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download "ner_random3_seed2" "${1}"
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python model_finetuning_ner.py -m "${1}" -d "ner_random3_seed2" --skip-train
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}
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fix "roberta-base"
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fix "vinai/bertweet-base"
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fix "jhu-clsp/bernice"
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fix "roberta-large"
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fix "vinai/bertweet-large"
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fix "cardiffnlp/twitter-roberta-base-2019-90m"
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fix "cardiffnlp/twitter-roberta-base-dec2020"
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fix "cardiffnlp/twitter-roberta-base-2021-124m"
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fix "cardiffnlp/twitter-roberta-base-2022-154m"
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fix "cardiffnlp/twitter-roberta-large-2022-154m"
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experiments/model_finetuning_ner.py
CHANGED
@@ -21,6 +21,8 @@ from transformers import AutoTokenizer, AutoModelForTokenClassification, Trainin
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from huggingface_hub import Repository
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logging.basicConfig(format="%(asctime)s %(levelname)-8s %(message)s", level=logging.INFO, datefmt="%Y-%m-%d %H:%M:%S")
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EVAL_STEP = 500
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RANDOM_SEED = 42
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N_TRIALS = 10
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from huggingface_hub import Repository
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logging.basicConfig(format="%(asctime)s %(levelname)-8s %(message)s", level=logging.INFO, datefmt="%Y-%m-%d %H:%M:%S")
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os.environ["WANDB_DISABLED"] = "true"
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EVAL_STEP = 500
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RANDOM_SEED = 42
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N_TRIALS = 10
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experiments/model_finetuning_nerd.py
CHANGED
@@ -21,6 +21,8 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification, Trai
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from huggingface_hub import Repository
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logging.basicConfig(format="%(asctime)s %(levelname)-8s %(message)s", level=logging.INFO, datefmt="%Y-%m-%d %H:%M:%S")
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EVAL_STEP = 500
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RANDOM_SEED = 42
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N_TRIALS = 10
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from huggingface_hub import Repository
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logging.basicConfig(format="%(asctime)s %(levelname)-8s %(message)s", level=logging.INFO, datefmt="%Y-%m-%d %H:%M:%S")
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os.environ["WANDB_DISABLED"] = "true"
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EVAL_STEP = 500
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RANDOM_SEED = 42
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N_TRIALS = 10
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experiments/model_finetuning_sentiment.py
CHANGED
@@ -21,6 +21,8 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification, Trai
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from huggingface_hub import Repository
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logging.basicConfig(format="%(asctime)s %(levelname)-8s %(message)s", level=logging.INFO, datefmt="%Y-%m-%d %H:%M:%S")
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EVAL_STEP = 500
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RANDOM_SEED = 42
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N_TRIALS = 10
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from huggingface_hub import Repository
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logging.basicConfig(format="%(asctime)s %(levelname)-8s %(message)s", level=logging.INFO, datefmt="%Y-%m-%d %H:%M:%S")
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os.environ["WANDB_DISABLED"] = "true"
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EVAL_STEP = 500
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RANDOM_SEED = 42
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N_TRIALS = 10
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experiments/requirements.txt
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@@ -10,4 +10,5 @@ accelerate==0.23.0
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evaluate==0.4.1
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sentencepiece==0.1.99
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protobuf==4.24.4
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seqeval==1.2.2
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evaluate==0.4.1
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sentencepiece==0.1.99
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protobuf==4.24.4
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seqeval==1.2.2
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wandb==0.16.0
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