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--- |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- generated_from_trainer , Lora adapter implement |
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metrics: |
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- wer |
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model-index: |
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- name: vi_whisper-small |
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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: vin100h |
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type: vin |
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config: Cleaned |
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split: Train 0.8 , Test 0.2 |
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metrics: |
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- name: Wer |
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type: wer |
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value: 21.68 |
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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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# vi_whisper-medium |
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This model is a one shot fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Vin100h dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2894 |
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- Wer: 21.68 on whisper-quantized model by CTranslate2 |
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# Model description |
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To use quantized model , firstly , read the doc of how to use CTranslate2 converter and Faster Whisper repo in here: |
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- [CTranslate2](https://github.com/OpenNMT/CTranslate2.git) |
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- [Faster-Whipser](https://github.com/guillaumekln/faster-whisper) |
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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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## 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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 1000 |
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- training_steps: 8000 |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 2.0.1+cu11.8 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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- PEFT 0.5.0.dev0 |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- load_in_8bit: True |
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- load_in_4bit: False |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: fp4 |
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- bnb_4bit_use_double_quant: False |
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- bnb_4bit_compute_dtype: float32 |
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