Keras Embedding Layer: InvalidArgumentError: indices[0,0] = 740 is not in [0, 13)

I get an error when training my model on an embedding layer:

InvalidArgumentError: indices[0,0] = 740 is not in [0, 13) [[Node: MM_emb/Gather = Gather[Tindices=DT_INT32, Tparams=DT_FLOAT, validate_indices=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](MM_emb/embeddings/read, MM_emb/Cast)]]

The code for the Embedding is:

def get_embedding(attr):
    name = str(attr)
    input_dims = len(categorical_features_mappings[attr])+1
    output_dims = category_embedding_sizes[attr]
    output_dims = (input_dims+1)//2
    if output_dims>50: output_dims=50

    inp = Input((1,), dtype='int64', name=name+'_in')
    u = Flatten(name=name+'_flt')(Embedding(input_dims, output_dims, name=name+'_emb',  embeddings_initializer='uniform')(inp))
    return inp,u


contin_inp = Input((len(continuous_features),), name='contin')
contin_out = Dense(len(continuous_features) * 10, activation='relu', name='contin_d')(contin_inp)
embeddings = [get_embedding(attr) for attr in category_embedding_sizes]

x = merge([emb for inp, emb in embeddings] + [contin_out], mode='concat')

x = Dropout(0.02)(x)
x = Dense(100, activation='relu', kernel_initializer='uniform')(x)
x = Dense(50, activation='relu', kernel_initializer='uniform')(x)
x = Dropout(0.2)(x)
x = Dense(1, activation='sigmoid')(x)

model = Model([inp for inp,emb in embeddings] + [contin_inp], x)

Anyone any idea?

Thanks!