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e748bc2
1
Parent(s):
c8de10b
reduced requirements
Browse files- environment.yml +0 -10
- models/utils.py +1 -5
- requirements.txt +0 -1
environment.yml
CHANGED
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@@ -8,15 +8,11 @@ dependencies:
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- python=3.10
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- pytorch
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- torchaudio
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- torchvision
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- librosa
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- numpy
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- pandas
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- seaborn
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- matplotlib
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- bs4
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- requests
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- bidict
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- tqdm
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- pytorch-lightning
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- rich
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@@ -25,9 +21,3 @@ dependencies:
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- transformers
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- accelerate
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- pytest
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-
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- pip:
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- evaluate
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- wakepy
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- soundfile
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- youtube_dl
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- python=3.10
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- pytorch
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- torchaudio
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- librosa
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- numpy
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- pandas
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- bs4
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- requests
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- tqdm
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- pytorch-lightning
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- rich
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- transformers
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- accelerate
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- pytest
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models/utils.py
CHANGED
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@@ -1,13 +1,9 @@
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import torch.nn as nn
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import torch
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import numpy as np
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import evaluate
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from sklearn.metrics import precision_score, recall_score, f1_score, accuracy_score
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accuracy = evaluate.load("accuracy")
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class LabelWeightedBCELoss(nn.Module):
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"""
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Binary Cross Entropy loss that assumes each float in the final dimension is a binary probability distribution.
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@@ -86,4 +82,4 @@ def get_id_label_mapping(labels: list[str]) -> tuple[dict, dict]:
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def compute_hf_metrics(eval_pred):
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predictions = np.argmax(eval_pred.predictions, axis=1)
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return
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import torch.nn as nn
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import torch
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import numpy as np
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from sklearn.metrics import precision_score, recall_score, f1_score, accuracy_score
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class LabelWeightedBCELoss(nn.Module):
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"""
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Binary Cross Entropy loss that assumes each float in the final dimension is a binary probability distribution.
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def compute_hf_metrics(eval_pred):
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predictions = np.argmax(eval_pred.predictions, axis=1)
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return accuracy_score(y_true=eval_pred.label_ids, y_pred=predictions)
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requirements.txt
CHANGED
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@@ -1,5 +1,4 @@
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torch
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torchvision
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torchaudio
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pytorch-lightning
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numpy
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torch
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torchaudio
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pytorch-lightning
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numpy
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