FileNotFoundError: [Errno 2] No such file or directory: 'checkpoints/best.pth'
hphuc4244 opened this issue · 4 comments
hphuc4244 commented
FileNotFoundError: [Errno 2] No such file or directory: 'checkpoints/best.pth'
manhph2211 commented
Hi @hphuc4244,
Usually, I won't push the checkpoint file into the repo cuz they might be too heavy. However, the checkpoint of the pretrained model of is quite good so you can even utilize it and train your custom dataset: https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h
Hope this help!
Max
hphuc4244 commented
Chào anh.
Anh có thể cho em xin riêng file checkpoint để huấn luyện.
Trân trọng cảm ơn anh
Vào CN, 5 thg 3, 2023 vào lúc 12:16 Max ***@***.***> đã
viết:
… Hi @hphuc4244 <https://github.com/hphuc4244>,
Usually, I won't push the checkpoint file into the repo cuz they might be
too heavy. However, the checkpoint of the pretrained model of is quite good
so you can even utilize it and train your custom dataset:
https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h
Hope this help!
Max
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haiquy572001 commented
Chào anh, anh có thể cho em xin file checkpoint để huấn luyện mô hình kh ạ, em cảm ơn ạ
manhph2211 commented
Hi 2 bạn nha, mình finetune theo bản pretrained này nè: https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h. Bạn có thể làm nhanh như sau:
import flash
from flash.audio import SpeechRecognition, SpeechRecognitionData
import torch
import sys
sys.path.append(".")
WAV2VEC_MODELS = ["facebook/wav2vec2-base-960h", "facebook/wav2vec2-large-960h-lv60", "nguyenvulebinh/wav2vec2-base-vietnamese-250h"]
# 1. Data
datamodule = SpeechRecognitionData.from_json(
"file",
"text",
train_file="train.json",
test_file="test.json",
batch_size=128,
)
# 2. Build the task
model = SpeechRecognition(backbone="nguyenvulebinh/wav2vec2-base-vietnamese-250h", processor_backbone = "nguyenvulebinh/wav2vec2-base-vietnamese-250h")
# # 3. Create the trainer and finetune the model if you want :)
trainer = flash.Trainer(max_epochs=5, gpus=0)
trainer.finetune(model, datamodule=datamodule, strategy="freeze")
# # 4. Predict on audio files!
datamodule = SpeechRecognitionData.from_files(predict_files=["demo/assets/database_sa1_Jan08_Mar19_cleaned_utt_0000000005-1.wav"], batch_size=1)
predictions = trainer.predict(model, datamodule=datamodule)
print(predictions)
# 5. Save the model!
# trainer.save_checkpoint("checkpoints/speech_recognition_model.pt")