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README.md
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---
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language:
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- cy
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license: apache-2.0
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base_model: facebook/wav2vec2-large-xlsr-53
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tags:
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- automatic-speech-recognition
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- python/custom_common_voice.py
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- generated_from_trainer
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datasets:
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- custom_common_voice
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metrics:
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- wer
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model-index:
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- name: wav2vec2-xlsr-53-ft-ccv-en-cy
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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: PYTHON/CUSTOM_COMMON_VOICE.PY - CY
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type: custom_common_voice
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config: cy
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split: validation
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args: 'Config: cy, Training split: train, Eval split: validation'
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metrics:
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- name: Wer
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type: wer
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value: 0.21777283505046477
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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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# wav2vec2-xlsr-53-ft-ccv-en-cy
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 0.
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## Model description
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 800
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- training_steps: 9000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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### Framework versions
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- Transformers 4.
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- Pytorch 2.
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- Datasets 2.
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- Tokenizers 0.
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-large-xlsr-53
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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: wav2vec2-xlsr-53-ft-ccv-en-cy
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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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# wav2vec2-xlsr-53-ft-ccv-en-cy
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2765
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- Wer: 0.2115
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## Model description
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 800
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- training_steps: 9000
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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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| 5.9898 | 0.25 | 500 | 1.3093 | 0.7971 |
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| 1.0749 | 0.5 | 1000 | 0.5816 | 0.4617 |
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| 0.4332 | 0.75 | 1500 | 0.4834 | 0.4091 |
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| 0.3303 | 1.01 | 2000 | 0.4203 | 0.3419 |
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| 0.276 | 1.26 | 2500 | 0.3910 | 0.3186 |
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| 0.2591 | 1.51 | 3000 | 0.3901 | 0.3067 |
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| 0.2501 | 1.76 | 3500 | 0.3646 | 0.2895 |
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| 0.224 | 2.01 | 4000 | 0.3517 | 0.2806 |
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| 0.182 | 2.26 | 4500 | 0.3348 | 0.2656 |
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| 0.1777 | 2.51 | 5000 | 0.3277 | 0.2612 |
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| 0.1734 | 2.77 | 5500 | 0.3323 | 0.2643 |
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| 0.1629 | 3.02 | 6000 | 0.3171 | 0.2485 |
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| 0.1338 | 3.27 | 6500 | 0.3103 | 0.2398 |
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| 0.1292 | 3.52 | 7000 | 0.2934 | 0.2268 |
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| 0.1264 | 3.77 | 7500 | 0.2923 | 0.2248 |
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| 0.118 | 4.02 | 8000 | 0.2880 | 0.2193 |
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| 0.0996 | 4.27 | 8500 | 0.2793 | 0.2124 |
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| 0.0969 | 4.52 | 9000 | 0.2765 | 0.2115 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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