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---
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license: apache-2.0
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base_model: openai/whisper-base.en
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: abbenedekwhisper-base.en-finetuning3-D3K
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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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# abbenedekwhisper-base.en-finetuning3-D3K
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This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.3880
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- Cer: 68.1692
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- Wer: 115.5629
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- Ser: 100.0
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- Cer Clean: 3.6171
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- Wer Clean: 6.2914
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- Ser Clean: 7.0175
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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: 5e-08
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- train_batch_size: 16
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- eval_batch_size: 64
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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: 10
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- training_steps: 2000
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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 | Cer | Wer | Ser | Cer Clean | Wer Clean | Ser Clean |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------:|:-----:|:---------:|:---------:|:---------:|
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| 7.3491 | 1.06 | 200 | 6.1358 | 64.7746 | 122.5166 | 100.0 | 3.2832 | 5.6291 | 7.0175 |
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| 6.162 | 2.13 | 400 | 5.2935 | 64.2181 | 119.8675 | 100.0 | 3.7284 | 6.6225 | 7.8947 |
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| 5.3192 | 3.19 | 600 | 4.7534 | 64.6633 | 119.2053 | 100.0 | 3.5058 | 6.2914 | 7.0175 |
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| 4.7266 | 4.26 | 800 | 4.3761 | 65.1085 | 118.2119 | 100.0 | 3.2832 | 5.9603 | 6.1404 |
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| 4.2728 | 5.32 | 1000 | 4.0472 | 65.9432 | 117.2185 | 100.0 | 3.2276 | 5.9603 | 6.1404 |
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| 3.9248 | 6.38 | 1200 | 3.7904 | 66.7223 | 116.2252 | 100.0 | 3.2276 | 5.9603 | 6.1404 |
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| 3.6714 | 7.45 | 1400 | 3.6008 | 67.8909 | 117.2185 | 100.0 | 3.1720 | 5.9603 | 6.1404 |
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| 3.499 | 8.51 | 1600 | 3.4790 | 69.0595 | 118.2119 | 100.0 | 3.1720 | 5.9603 | 6.1404 |
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| 3.393 | 9.57 | 1800 | 3.4106 | 68.9482 | 117.5497 | 100.0 | 3.1720 | 5.9603 | 6.1404 |
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| 3.3491 | 10.64 | 2000 | 3.3880 | 68.1692 | 115.5629 | 100.0 | 3.6171 | 6.2914 | 7.0175 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.2.2+cu121
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- Datasets 2.14.5
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- Tokenizers 0.15.2
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