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Update results.py
Browse files- results.py +46 -27
results.py
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@@ -422,50 +422,69 @@ llama_graph2 = fig
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#llama graph 4
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# Data for different buckets and years
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data = {
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"perplexities": [
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},
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"perplexities": [
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"perplexities": [9.
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"perplexities": [9.
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"perplexities": [9.
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"perplexities": [
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}
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}
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# Create figure
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# Add traces for each
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for
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# Update layout
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title="Perplexity Across Different
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xaxis_title="
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yaxis_title="Average Perplexity",
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legend_title="
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)
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# Show the figure
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llama_graph4 =
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##llama graph 5
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#llama graph 4
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# Data for different buckets and years
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import plotly.graph_objects as go
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# Data for different years and buckets
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data = {
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"2014": {
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"buckets": ["1-1", "2-5", "6-10", "11-100", "101-1000", "1001-30000000"],
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"perplexities": [9.276942939297756, 8.69938211424056, 8.158271167692497, 8.367670702299348, 6.583755343348351, 7.497674909399879]
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},
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"2015": {
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"buckets": ["1-1", "2-5", "6-10", "11-100", "101-1000", "1001-30000000"],
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"perplexities": [9.103981560121444, 8.198551019737206, 8.17752561770772, 8.233928498586414, 6.517481691960036, 7.3736492145399355]
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},
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"2016": {
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"buckets": ["1-1", "2-5", "6-10", "11-100", "101-1000", "1001-30000000"],
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"perplexities": [9.023271012270133, 8.067050538323626, 8.150103850870096, 8.232721560484496, 6.3749350052179015, 7.350697996200808]
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},
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"2017": {
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"buckets": ["1-1", "2-5", "6-10", "11-100", "101-1000", "1001-30000000"],
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"perplexities": [9.129487810210167, 8.290815319993621, 7.878257519772607, 7.98292071692709, 6.524893452272168, 6.918924770013169]
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},
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"2018": {
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"buckets": ["1-1", "2-5", "6-10", "11-100", "101-1000", "1001-30000000"],
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"perplexities": [9.213411471804902, 7.89026459259236, 7.403516159589743, 7.556076611087452, 6.6509342133282745, 6.493818412135467]
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},
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"2019": {
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"buckets": ["1-1", "2-5", "6-10", "11-100", "101-1000", "1001-30000000"],
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"perplexities": [8.96407327327958, 7.628975687395983, 7.036189728869401, 6.6349379440939895, 6.446837262269017, 6.086615106309735]
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},
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"2020": {
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"buckets": ["1-1", "2-5", "6-10", "11-100", "101-1000", "1001-30000000"],
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"perplexities": [9.137673180826452, 7.794611238323424, 7.059198583303955, 6.82070782491814, 6.64418110544852, 6.271177318179787]
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},
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"2021": {
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"buckets": ["1-1", "2-5", "6-10", "11-100", "101-1000", "1001-30000000"],
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"perplexities": [9.178752781806578, 7.70543845537127, 6.698443323550492, 6.472409310902069, 7.307749809853384, 6.782598533191676]
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},
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"2022": {
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"buckets": ["1-1", "2-5", "6-10", "11-100", "101-1000", "1001-30000000"],
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"perplexities": [9.096031774523855, 7.652072280274248, 6.615135590934534, 6.239500427643811, 6.787412545253696, 6.99638904682498]
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},
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"2023": {
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"buckets": ["1-1", "2-5", "6-10", "11-100", "101-1000", "1001-30000000"],
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"perplexities": [8.728460642325789, 7.561677894180029, 6.194391269071906, 5.775947387872692, 6.054439209079063, 5.3384410032299]
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}
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}
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# Create figure
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fig = go.Figure()
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# Add traces for each year
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for year, year_data in data.items():
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fig.add_trace(go.Scatter(x=year_data["buckets"], y=year_data["perplexities"], mode='lines+markers', name=year))
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# Update layout
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fig.update_layout(
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title="Perplexity Across Different Buckets (Local)",
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xaxis_title="Bucket (Duplicate Count Range)",
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yaxis_title="Average Perplexity",
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legend_title="Year"
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)
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# Show the figure
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llama_graph4 = fig
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##llama graph 5
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