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license: apache-2.0 |
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tags: |
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- audio-classification |
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- generated_from_trainer |
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datasets: |
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- xtreme_s |
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metrics: |
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- accuracy |
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base_model: openai/whisper-medium |
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model-index: |
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- name: whisper-medium-fleurs-lang-id |
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results: [] |
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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 Medium FLEURS Language Identification |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the [FLEURS subset](https://huggingface.co/datasets/google/xtreme_s#language-identification---fleurs-langid) of the [google/xtreme_s](https://huggingface.co/google/xtreme_s) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8413 |
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- Accuracy: 0.8805 |
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To reproduce this run, execute the command in [`run.sh`](https://huggingface.co/sanchit-gandhi/whisper-medium-fleurs-lang-id/blob/main/run.sh). |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 0 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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_ratio: 0.1 |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 0.0152 | 1.0 | 8494 | 0.9087 | 0.8431 | |
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| 0.0003 | 2.0 | 16988 | 1.0059 | 0.8460 | |
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| 0.0 | 3.0 | 25482 | 0.8413 | 0.8805 | |
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### Framework versions |
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- Transformers 4.27.0.dev0 |
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- Pytorch 1.13.1 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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