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Update results.py
Browse files- results.py +1 -3
results.py
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@@ -9,8 +9,6 @@ import plotly.express as px
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##upsampling validation loss graph
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import plotly.graph_objects as go
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# Data
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steps = [5000, 10000, 15000, 20000, 25000, 30000, 35000, 40000, 45000, 50000,
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55000, 60000, 65000, 70000, 75000, 80000, 85000, 90000, 95000, 100000,
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@@ -747,7 +745,7 @@ upsampling_exp = Div(
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P("To account for differing dataset sizes, the evaluation scores represent the final evaluation score after the entire dataset has been processed."),
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H3("Training Evaluations"),
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P("We also conducted full scale training using TxT360 and FineWeb-1.5T. Below are plots of the training and validation loss curves for each dataset. We can see that TxT360 achieves a lower training and validation loss compared to FineWeb-1.5T. "),
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validation_loss_graph,
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)
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perp1_div = Div(
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##upsampling validation loss graph
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# Data
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steps = [5000, 10000, 15000, 20000, 25000, 30000, 35000, 40000, 45000, 50000,
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55000, 60000, 65000, 70000, 75000, 80000, 85000, 90000, 95000, 100000,
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P("To account for differing dataset sizes, the evaluation scores represent the final evaluation score after the entire dataset has been processed."),
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H3("Training Evaluations"),
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P("We also conducted full scale training using TxT360 and FineWeb-1.5T. Below are plots of the training and validation loss curves for each dataset. We can see that TxT360 achieves a lower training and validation loss compared to FineWeb-1.5T. "),
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plotly2fasthtml(validation_loss_graph),
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)
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perp1_div = Div(
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