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README.md
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---
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base_model: openai/whisper-small
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datasets:
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- common_voice_16_1
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library_name: peft
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: whisper-small-finetuned_v1-finetuned
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/keviinkibe/huggingface/runs/2zbk30rr)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/keviinkibe/huggingface/runs/2zbk30rr)
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# whisper-small-finetuned_v1-finetuned
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_16_1 dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 2.8895
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- eval_wer: 122.8661
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- eval_runtime: 654.6896
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- eval_samples_per_second: 0.764
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- eval_steps_per_second: 0.024
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- epoch: 0.1667
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- step: 50
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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: 0.0003
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- train_batch_size: 32
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- eval_batch_size: 32
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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: 50
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- training_steps: 300
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- mixed_precision_training: Native AMP
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### Framework versions
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- PEFT 0.11.1
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- Transformers 4.42.3
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- Pytorch 2.2.2+cu121
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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