Petr Tsvetkov
commited on
Commit
β’
2d03034
1
Parent(s):
e027012
Update the parameters
Browse files
generation_steps/examples.py
CHANGED
@@ -1,7 +1,7 @@
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import config
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from api_wrappers import hf_data_loader
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N_EXAMPLES =
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def get_example_prompt_end_to_start(start_msg, end_msg):
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import config
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from api_wrappers import hf_data_loader
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N_EXAMPLES = 15
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def get_example_prompt_end_to_start(start_msg, end_msg):
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generation_steps/metrics_analysis.py
CHANGED
@@ -34,6 +34,10 @@ def rouge2_fn(pred, ref):
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return ROUGE.compute(predictions=[pred], references=[ref])["rouge2"]
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BERTSCORE = evaluate.load('bertscore', cache_dir=config.CACHE_DIR)
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@@ -45,13 +49,30 @@ def gptscore_fn(pred, ref):
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return gpt_eval.compute(prediction=pred, reference=ref)
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METRICS = {
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"gptscore": gptscore_fn,
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"bleu": bleu_fn,
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"meteor": meteor_fn,
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"rouge1": rouge1_fn,
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"rouge2": rouge2_fn,
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"bertscore": bertscore_fn,
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}
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@@ -98,6 +119,13 @@ def correlations_for_group(group):
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f"{metric}_pearson": group[f"{metric}_related"].corr(group[f"{metric}_independent"], method="pearson"),
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f"{metric}_spearman": group[f"{metric}_related"].corr(group[f"{metric}_independent"], method="spearman")
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})
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return pd.Series(functools.reduce(operator.ior, correlations, {}))
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return ROUGE.compute(predictions=[pred], references=[ref])["rouge2"]
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def rougeL_fn(pred, ref):
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return ROUGE.compute(predictions=[pred], references=[ref])["rougeL"]
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BERTSCORE = evaluate.load('bertscore', cache_dir=config.CACHE_DIR)
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return gpt_eval.compute(prediction=pred, reference=ref)
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CHRF = evaluate.load("chrf")
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def chrf_fn(pred, ref):
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return CHRF.compute(predictions=[pred], references=[[ref]])["score"]
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TER = evaluate.load("ter")
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def ter_fn(pred, ref):
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return TER.compute(predictions=[pred], references=[[ref]])["score"]
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METRICS = {
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# "gptscore": gptscore_fn,
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"bleu": bleu_fn,
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"meteor": meteor_fn,
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"rouge1": rouge1_fn,
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"rouge2": rouge2_fn,
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"rougeL": rougeL_fn,
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"bertscore": bertscore_fn,
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"chrF": chrf_fn,
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"ter": ter_fn
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}
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f"{metric}_pearson": group[f"{metric}_related"].corr(group[f"{metric}_independent"], method="pearson"),
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f"{metric}_spearman": group[f"{metric}_related"].corr(group[f"{metric}_independent"], method="spearman")
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})
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for other_metric in METRICS:
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correlations.append({
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f"ind_{metric}_rel_{other_metric}_pearson": group[f"{other_metric}_related"].corr(
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group[f"{metric}_independent"], method="pearson"),
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f"ind_{metric}_rel_{other_metric}_spearman": group[f"{other_metric}_related"].corr(
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group[f"{metric}_independent"], method="spearman")
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})
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return pd.Series(functools.reduce(operator.ior, correlations, {}))
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generation_steps/synthetic_end_to_start.py
CHANGED
@@ -7,7 +7,7 @@ import statistics
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from api_wrappers import grazie_wrapper, hf_data_loader
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from generation_steps import examples
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GENERATION_MULTIPLIER =
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REL_INSERTIONS_THRESHOLD = 0.5
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GENERATION_ATTEMPTS = 5
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from api_wrappers import grazie_wrapper, hf_data_loader
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from generation_steps import examples
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GENERATION_MULTIPLIER = 2
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REL_INSERTIONS_THRESHOLD = 0.5
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GENERATION_ATTEMPTS = 5
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generation_steps/synthetic_start_to_end.py
CHANGED
@@ -7,7 +7,7 @@ import statistics
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from api_wrappers import grazie_wrapper
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from generation_steps import examples
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GENERATION_MULTIPLIER =
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REL_DELETIONS_THRESHOLD = 0.75
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GENERATION_ATTEMPTS = 5
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from api_wrappers import grazie_wrapper
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from generation_steps import examples
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GENERATION_MULTIPLIER = 2
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REL_DELETIONS_THRESHOLD = 0.75
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GENERATION_ATTEMPTS = 5
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