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- fine-tune-whisper-streaming.ipynb +42 -6
README.md
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---
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language:
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- vi
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license: apache-2.0
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tags:
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- whisper-event
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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model-index:
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- name: Whisper large v2 vi
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: common_voice_11_0
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type: mozilla-foundation/common_voice_11_0
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config: vi
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split: test
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args: vi
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metrics:
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- name: Wer
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type: wer
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value: 17.076113182715506
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Whisper large v2 vi
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_11_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5530
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- Wer: 17.0761
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 50
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- training_steps: 300
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.0012 | 21.01 | 150 | 0.5211 | 17.2845 |
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| 0.0006 | 42.02 | 300 | 0.5530 | 17.0761 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.8.1.dev0
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- Tokenizers 0.13.2
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fine-tune-whisper-streaming.ipynb
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"id": "ee8b7b8e-1c9a-4d77-9137-1778a629e6de",
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"metadata": {},
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"outputs": [
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" <progress value='
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" [300/300
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" </div>\n",
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" <table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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"Feature extractor saved in ./preprocessor_config.json\n",
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"tokenizer config file saved in ./tokenizer_config.json\n",
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"Special tokens file saved in ./special_tokens_map.json\n",
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"added tokens file saved in ./added_tokens.json\n"
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}
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"source": [
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"cell_type": "code",
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"id": "6dd0e310-9b07-4133-ac14-2ed2d7524e22",
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"metadata": {},
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"outputs": [],
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"execution_count": null,
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"id": "95737cda-c5dd-4887-a4d0-dfcb0d61d977",
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"metadata": {},
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"outputs": [
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"source": [
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"trainer.push_to_hub(**kwargs)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"id": "ee8b7b8e-1c9a-4d77-9137-1778a629e6de",
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"metadata": {},
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"outputs": [
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"\n",
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" <div>\n",
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" \n",
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" <progress value='300' max='300' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
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" [300/300 2:15:47, Epoch 42/9223372036854775807]\n",
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" </div>\n",
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" <table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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"Feature extractor saved in ./preprocessor_config.json\n",
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"tokenizer config file saved in ./tokenizer_config.json\n",
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"Special tokens file saved in ./special_tokens_map.json\n",
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"added tokens file saved in ./added_tokens.json\n",
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"\n",
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"\n",
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"Training completed. Do not forget to share your model on huggingface.co/models =)\n",
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"\n",
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"\n",
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"Loading best model from ./checkpoint-300 (score: 17.076113182715506).\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"TrainOutput(global_step=300, training_loss=0.27811144128490317, metrics={'train_runtime': 8190.4014, 'train_samples_per_second': 2.344, 'train_steps_per_second': 0.037, 'total_flos': 4.50451963772928e+19, 'train_loss': 0.27811144128490317, 'epoch': 42.02})"
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]
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},
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"execution_count": 22,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"cell_type": "code",
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"execution_count": 23,
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"id": "6dd0e310-9b07-4133-ac14-2ed2d7524e22",
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"metadata": {},
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"outputs": [],
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"execution_count": null,
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"id": "95737cda-c5dd-4887-a4d0-dfcb0d61d977",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Saving model checkpoint to ./\n",
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"Configuration saved in ./config.json\n",
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"Model weights saved in ./pytorch_model.bin\n",
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"Feature extractor saved in ./preprocessor_config.json\n",
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"tokenizer config file saved in ./tokenizer_config.json\n",
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"Special tokens file saved in ./special_tokens_map.json\n",
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"added tokens file saved in ./added_tokens.json\n",
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"Several commits (2) will be pushed upstream.\n",
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"The progress bars may be unreliable.\n",
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"Upload file pytorch_model.bin: 0%| | 1.00/5.75G [00:00<?, ?B/s]\n",
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"Upload file runs/Dec20_16-04-54_129-146-50-243/events.out.tfevents.1671552308.129-146-50-243.731508.0: 0%| | 1.00/50.8\u001b[A\n",
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"Upload file runs/Dec20_16-04-54_129-146-50-243/events.out.tfevents.1671552308.129-146-50-243.731508.0: 4.66GB [00:01, 4.99GB/s]\u001b[A\n",
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"Upload file runs/Dec20_16-04-54_129-146-50-243/events.out.tfevents.1671552308.129-146-50-243.731508.0: 4.66GB [00:14, 4.99GB/s]\u001b[A"
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]
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}
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],
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"source": [
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"trainer.push_to_hub(**kwargs)"
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]
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