David Pomerenke
commited on
Commit
·
1b634f3
1
Parent(s):
1167b2d
For classification use number + few-shot
Browse files(rather than label, where the label is in English)
- evals.py +12 -12
- results.json +342 -79
evals.py
CHANGED
@@ -27,7 +27,7 @@ models = [
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"mistralai/mistral-small-24b-instruct-2501", # 0.14$/M tokens
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"google/gemini-2.0-flash-001", # 0.4$/M tokens
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# "qwen/qwen-turbo", # 0.2$/M tokens; recognizes "inappropriate content"
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-
"deepseek/deepseek-chat", # 0.9$/M tokens
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"microsoft/phi-4", # 0.07$/M tokens
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]
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fast_model = "meta-llama/llama-3.3-70b-instruct"
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@@ -139,7 +139,7 @@ languages = pd.merge(
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) # "left" because keep it simple for now
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languages["in_benchmark"] = languages["bcp_47"].isin(benchmark_languages["bcp_47"])
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-
languages = languages.sort_values(by="speakers", ascending=False).iloc[:
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# sample languages to translate to
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target_languages = languages[languages["in_benchmark"]].sample(
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@@ -238,16 +238,13 @@ async def classify_and_evaluate(model, language_bcp_47, nr):
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frac=1, random_state=42
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)
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test_paragraph = test_paragraphs.iloc[nr]
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-
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-
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-
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-
"content": f"Categories: {'; '.join(examples['topic'].drop_duplicates())}.",
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-
}
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-
]
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for example in examples.itertuples():
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messages += [
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{"role": "user", "content": example.text},
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-
{"role": "assistant", "content": example.topic},
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]
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reply = await complete(
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model=model,
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@@ -259,13 +256,16 @@ async def classify_and_evaluate(model, language_bcp_47, nr):
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},
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],
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temperature=0,
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-
max_tokens=
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)
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-
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return {
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"model": model,
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"bcp_47": language["bcp_47"],
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-
"true": test_paragraph.topic,
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"pred": prediction,
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"sentence_nr": nr,
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}
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"mistralai/mistral-small-24b-instruct-2501", # 0.14$/M tokens
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"google/gemini-2.0-flash-001", # 0.4$/M tokens
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# "qwen/qwen-turbo", # 0.2$/M tokens; recognizes "inappropriate content"
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+
# "deepseek/deepseek-chat", # 0.9$/M tokens
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"microsoft/phi-4", # 0.07$/M tokens
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]
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fast_model = "meta-llama/llama-3.3-70b-instruct"
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) # "left" because keep it simple for now
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languages["in_benchmark"] = languages["bcp_47"].isin(benchmark_languages["bcp_47"])
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+
languages = languages.sort_values(by="speakers", ascending=False).iloc[:20]
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# sample languages to translate to
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target_languages = languages[languages["in_benchmark"]].sample(
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frac=1, random_state=42
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)
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test_paragraph = test_paragraphs.iloc[nr]
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+
def topic_to_number(topic):
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+
return top_topics.get_loc(topic)
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+
messages = []
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for example in examples.itertuples():
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messages += [
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{"role": "user", "content": example.text},
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+
{"role": "assistant", "content": str(topic_to_number(example.topic))},
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]
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reply = await complete(
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model=model,
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},
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],
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temperature=0,
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+
max_tokens=5,
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)
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+
try:
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+
prediction = int(reply.choices[0].message.content.strip())
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+
except ValueError:
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+
prediction = -1
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return {
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"model": model,
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"bcp_47": language["bcp_47"],
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+
"true": topic_to_number(test_paragraph.topic),
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"pred": prediction,
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"sentence_nr": nr,
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}
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results.json
CHANGED
@@ -4,18 +4,46 @@
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"bcp_47": "en",
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"speakers": 1636485840,
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"scores": [
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{
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.4351349353198866,
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"chrf": 54.9504915580248,
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-
"accuracy":
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-
"overall_score": 0.
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}
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],
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-
"bleu": 0.
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-
"chrf":
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-
"accuracy":
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-
"overall_score": 0.
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"commonvoice_hours": 2651.0,
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"commonvoice_locale": "en",
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"population": {
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@@ -185,14 +213,14 @@
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.3977775857451761,
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"chrf": 57.672913792439125,
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-
"accuracy":
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-
"overall_score": 0.
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}
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],
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"bleu": 0.3977775857451761,
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"chrf": 57.672913792439125,
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-
"accuracy":
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-
"overall_score": 0.
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"commonvoice_hours": 422.0,
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"commonvoice_locale": "zh-TW",
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"population": {
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@@ -227,14 +255,14 @@
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.333521621016373,
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"chrf": 50.48364584189306,
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-
"accuracy": 0.
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-
"overall_score": 0.
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}
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],
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"bleu": 0.333521621016373,
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"chrf": 50.48364584189306,
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-
"accuracy": 0.
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-
"overall_score": 0.
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"commonvoice_hours": 16.0,
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"commonvoice_locale": "hi-IN",
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"population": {
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@@ -255,14 +283,14 @@
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.29160032861883095,
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"chrf": 47.668399832701844,
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-
"accuracy": 0.
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-
"overall_score": 0.
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}
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],
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"bleu": 0.29160032861883095,
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"chrf": 47.668399832701844,
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-
"accuracy": 0.
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-
"overall_score": 0.
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"commonvoice_hours": 446.0,
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"commonvoice_locale": "es",
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"population": {
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@@ -316,14 +344,14 @@
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.277257629790728,
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"chrf": 46.62779335380641,
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-
"accuracy": 0.
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-
"overall_score": 0.
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}
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],
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"bleu": 0.277257629790728,
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"chrf": 46.62779335380641,
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-
"accuracy": 0.
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-
"overall_score": 0.
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"commonvoice_hours": 91.0,
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"commonvoice_locale": "ar",
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"population": {
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@@ -376,14 +404,14 @@
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.2659144372728079,
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"chrf": 44.14831240898717,
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-
"accuracy": 0.
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-
"overall_score": 0.
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}
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],
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"bleu": 0.2659144372728079,
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"chrf": 44.14831240898717,
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-
"accuracy": 0.
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-
"overall_score": 0.
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"commonvoice_hours": 77.0,
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"commonvoice_locale": "ur",
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"population": {
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@@ -403,14 +431,14 @@
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.315663773358301,
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"chrf": 49.253978669350964,
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-
"accuracy": 0.
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-
"overall_score": 0.
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}
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],
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"bleu": 0.315663773358301,
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"chrf": 49.253978669350964,
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-
"accuracy": 0.
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-
"overall_score": 0.
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"commonvoice_hours": 1052.0,
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"commonvoice_locale": "fr",
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"population": {
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@@ -487,14 +515,14 @@
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.21265887286151353,
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"chrf": 41.501657722373686,
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-
"accuracy": 0.
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-
"overall_score": 0.
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}
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],
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"bleu": 0.21265887286151353,
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"chrf": 41.501657722373686,
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-
"accuracy": 0.
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-
"overall_score": 0.
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"commonvoice_hours": 49.0,
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"commonvoice_locale": "bn",
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"population": {
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@@ -510,53 +538,18 @@
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"bcp_47": "pt",
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"speakers": 237496885,
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"scores": [
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-
{
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-
"model": "openai/gpt-4o-mini",
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-
"bleu": 0.37370265193281843,
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-
"chrf": 57.010201314973216,
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-
"accuracy": 0.9666666666666667,
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-
"overall_score": 0.6701846592997426
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-
},
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{
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.27514792195783394,
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"chrf": 45.901248962808694,
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-
"accuracy": 0.
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-
"overall_score": 0.
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-
},
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-
{
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-
"model": "mistralai/mistral-small-24b-instruct-2501",
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-
"bleu": 0.3691905380990064,
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-
"chrf": 54.842418095352954,
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-
"accuracy": 0.9666666666666667,
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-
"overall_score": 0.6679286023828366
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-
},
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-
{
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-
"model": "google/gemini-2.0-flash-001",
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-
"bleu": 0.4020145367576223,
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-
"chrf": 60.73156386707501,
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-
"accuracy": 0.9,
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-
"overall_score": 0.6510072683788112
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-
},
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-
{
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-
"model": "deepseek/deepseek-chat",
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-
"bleu": 0.39831859400698993,
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-
"chrf": 59.99225659809846,
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-
"accuracy": 0.9666666666666667,
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-
"overall_score": 0.6824926303368283
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-
},
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-
{
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-
"model": "microsoft/phi-4",
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-
"bleu": 0.35576182901107084,
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-
"chrf": 56.05856754270042,
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-
"accuracy": 0.9,
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-
"overall_score": 0.6278809145055354
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}
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],
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-
"bleu": 0.
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-
"chrf":
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-
"accuracy": 0.
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-
"overall_score": 0.
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"commonvoice_hours": 177.0,
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"commonvoice_locale": "pt",
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"population": {
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@@ -587,14 +580,14 @@
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.3048037308116852,
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"chrf": 48.4304965568793,
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-
"accuracy": 0.
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-
"overall_score": 0.
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}
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],
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"bleu": 0.3048037308116852,
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"chrf": 48.4304965568793,
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-
"accuracy": 0.
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-
"overall_score": 0.
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"commonvoice_hours": 2.3,
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"commonvoice_locale": "pa-IN",
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"population": {
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@@ -605,5 +598,275 @@
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"PK": 163450700,
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"SG": 9314
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}
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}
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]
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"bcp_47": "en",
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"speakers": 1636485840,
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"scores": [
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+
{
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+
"model": "openai/gpt-4o-mini",
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+
"bleu": 0.89404322120213,
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"chrf": 92.53933977489264,
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+
"accuracy": 0.5666666666666667,
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+
"overall_score": 0.7303549439343984
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+
},
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{
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"model": "meta-llama/llama-3.3-70b-instruct",
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"bleu": 0.4351349353198866,
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"chrf": 54.9504915580248,
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+
"accuracy": 0.6,
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+
"overall_score": 0.5175674676599433
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+
},
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+
{
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"model": "mistralai/mistral-small-24b-instruct-2501",
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"bleu": 0.8800468872938262,
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+
"chrf": 94.30164664106223,
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+
"accuracy": 0.5333333333333333,
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+
"overall_score": 0.7066901103135798
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+
},
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+
{
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+
"model": "google/gemini-2.0-flash-001",
|
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+
"bleu": 0.8489646963773831,
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+
"chrf": 92.73129066280984,
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+
"accuracy": 0.8666666666666667,
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+
"overall_score": 0.8578156815220249
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+
},
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+
{
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+
"model": "microsoft/phi-4",
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