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27 lines
791 B
Python
27 lines
791 B
Python
import glob
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import pickle
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import numpy as np
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from matplotlib import pyplot as plt
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plt.figure()
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for fpath in glob.glob('./eval_data/*.pkl'):
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parts = fpath.split('__')
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model_name = parts[1].replace('model-', '').replace('.pkl', '')
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lora_name = parts[2].replace('lora-', '').replace('.pkl', '')
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with open(fpath, 'rb') as f:
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data = pickle.load(f)
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perplexities = data['perplexities']
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perplexities = np.nan_to_num(perplexities, 100)
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perplexities = np.clip(perplexities, 0, 100)
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if 'nomic' in fpath:
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label = 'GPT4all-lora'
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else:
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label = 'alpaca-lora'
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plt.hist(perplexities, label=label, alpha=.5)
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plt.xlabel('Perplexity')
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plt.ylabel('Frequency')
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plt.legend()
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plt.savefig('figs/perplexity_hist.png')
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