kiddojazz

#from tensorflow.keras.callbacks import EarlyStopping
 
early_stopping = tf.keras.callbacks.EarlyStopping(monitor='val_loss', patience=3, restore_best_weights=True)
 
model.fit(train_dataset.shuffle(1000).batch(16),
epochs=2,
batch_size=16,
validation_data=val_dataset.shuffle(1000).batch(16),
callbacks=[early_stopping])

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model = TFDistilBertForSequenceClassification.from_pretrained('distilbert-base-uncased', num_labels=5)
 
optimizer = tf.keras.optimizers.Adam(learning_rate=5e-5, epsilon=1e-08)
model.compile(optimizer=optimizer, loss=model.hf_compute_loss, metrics=['accuracy'])

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train_dataset = tf.data.Dataset.from_tensor_slices((
dict(train_encodings),
train_labels
))
val_dataset = tf.data.Dataset.from_tensor_slices((
dict(val_encodings),
val_labels
))

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tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')
train_encodings = tokenizer(train_texts, truncation=True, padding=True)
val_encodings = tokenizer(val_texts, truncation=True, padding=True)

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from sklearn.model_selection import train_test_split
 
# Split Train and Validation data
train_texts, val_texts, train_labels, val_labels = train_test_split(data_texts, data_labels, test_size=0.2, random_state=0, shuffle=True)
 
# Keep some data for inference (testing)
train_texts, test_texts, train_labels, test_labels = train_test_split(train_texts, train_labels, test_size=0.01, random_state=0, shuffle=True)

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url = 'https://github.com/kiddojazz/Multitext-Classification/blob/master/bbc_data.csv?raw=true'
#df = pd.read_csv(url,index_col=0)
df = pd.read_csv(url)
print(df.head(5))

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from transformers import DistilBertTokenizer
from transformers import TFDistilBertForSequenceClassification
import tensorflow as tf
import pandas as pd

kiddojazz

select * from(
select customer_id, state_, profit_total,
rank() over(partition by state_ order by profit_total desc) as Rank_row
from customer_order_window) as rank_info
where rank_row = 1;

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select customer_id, state_, profit_total,
first_value(profit_total) over(partition by state_ order by profit_total desc) as first_row
from customer_order_window;

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select customer_id, state_, profit_total,
LEAD(profit_total) over(partition by state_ order by profit_total desc) as Lead_row
from customer_order_window;