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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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- automatic-speech-recognition |
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- DewiBrynJones/banc-trawsgrifiadau-bangor-clean-with-ccv |
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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-btb-ccv-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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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-xlsr-53-ft-btb-ccv-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 the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-CLEAN-WITH-CCV - DEFAULT dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5355 |
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- Wer: 0.4186 |
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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: 8 |
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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: 500 |
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- training_steps: 3000 |
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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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| No log | 0.0194 | 100 | 3.5494 | 1.0 | |
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| No log | 0.0387 | 200 | 3.0426 | 1.0 | |
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| No log | 0.0581 | 300 | 2.8965 | 1.0 | |
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| No log | 0.0774 | 400 | 1.8263 | 0.9829 | |
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| 3.9715 | 0.0968 | 500 | 1.3860 | 0.8749 | |
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| 3.9715 | 0.1161 | 600 | 1.3084 | 0.8153 | |
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| 3.9715 | 0.1355 | 700 | 1.0550 | 0.7337 | |
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| 3.9715 | 0.1549 | 800 | 1.0012 | 0.7190 | |
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| 3.9715 | 0.1742 | 900 | 0.9137 | 0.6752 | |
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| 1.0155 | 0.1936 | 1000 | 0.8486 | 0.6469 | |
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| 1.0155 | 0.2129 | 1100 | 0.8535 | 0.6112 | |
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| 1.0155 | 0.2323 | 1200 | 0.8350 | 0.6193 | |
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| 1.0155 | 0.2516 | 1300 | 0.7681 | 0.5670 | |
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| 1.0155 | 0.2710 | 1400 | 0.7377 | 0.5559 | |
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| 0.7987 | 0.2904 | 1500 | 0.7130 | 0.5437 | |
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| 0.7987 | 0.3097 | 1600 | 0.7040 | 0.5452 | |
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| 0.7987 | 0.3291 | 1700 | 0.6729 | 0.5051 | |
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| 0.7987 | 0.3484 | 1800 | 0.6646 | 0.5113 | |
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| 0.7987 | 0.3678 | 1900 | 0.6531 | 0.4969 | |
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| 0.6851 | 0.3871 | 2000 | 0.6414 | 0.5038 | |
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| 0.6851 | 0.4065 | 2100 | 0.6109 | 0.4677 | |
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| 0.6851 | 0.4259 | 2200 | 0.6035 | 0.4692 | |
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| 0.6851 | 0.4452 | 2300 | 0.5802 | 0.4590 | |
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| 0.6851 | 0.4646 | 2400 | 0.5720 | 0.4455 | |
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| 0.5979 | 0.4839 | 2500 | 0.5695 | 0.4426 | |
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| 0.5979 | 0.5033 | 2600 | 0.5557 | 0.4351 | |
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| 0.5979 | 0.5226 | 2700 | 0.5499 | 0.4270 | |
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| 0.5979 | 0.5420 | 2800 | 0.5451 | 0.4258 | |
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| 0.5979 | 0.5614 | 2900 | 0.5383 | 0.4217 | |
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| 0.5753 | 0.5807 | 3000 | 0.5355 | 0.4186 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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