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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: 0.4593 |
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- Wer: 0.3553 |
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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: 64 |
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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: 2600 |
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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 | 0.0566 | 100 | 3.5994 | 1.0 | |
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| No log | 0.1133 | 200 | 3.0224 | 1.0 | |
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| No log | 0.1699 | 300 | 1.9627 | 0.9061 | |
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| No log | 0.2265 | 400 | 0.9921 | 0.6952 | |
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| 3.6184 | 0.2831 | 500 | 0.8504 | 0.6158 | |
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| 3.6184 | 0.3398 | 600 | 0.7936 | 0.5964 | |
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| 3.6184 | 0.3964 | 700 | 0.7601 | 0.5606 | |
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| 3.6184 | 0.4530 | 800 | 0.6909 | 0.5128 | |
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| 3.6184 | 0.5096 | 900 | 0.6617 | 0.4916 | |
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| 0.4662 | 0.5663 | 1000 | 0.6467 | 0.4812 | |
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| 0.4662 | 0.6229 | 1100 | 0.6144 | 0.4639 | |
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| 0.4662 | 0.6795 | 1200 | 0.5942 | 0.4537 | |
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| 0.4662 | 0.7361 | 1300 | 0.5675 | 0.4351 | |
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| 0.4662 | 0.7928 | 1400 | 0.5539 | 0.4230 | |
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| 0.3508 | 0.8494 | 1500 | 0.5448 | 0.4144 | |
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| 0.3508 | 0.9060 | 1600 | 0.5326 | 0.4066 | |
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| 0.3508 | 0.9626 | 1700 | 0.5155 | 0.3989 | |
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| 0.3508 | 1.0193 | 1800 | 0.5067 | 0.3856 | |
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| 0.3508 | 1.0759 | 1900 | 0.4916 | 0.3724 | |
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| 0.2774 | 1.1325 | 2000 | 0.4855 | 0.3697 | |
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| 0.2774 | 1.1891 | 2100 | 0.4798 | 0.3661 | |
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| 0.2774 | 1.2458 | 2200 | 0.4774 | 0.3646 | |
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| 0.2774 | 1.3024 | 2300 | 0.4699 | 0.3585 | |
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| 0.2774 | 1.3590 | 2400 | 0.4651 | 0.3550 | |
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| 0.2328 | 1.4156 | 2500 | 0.4611 | 0.3570 | |
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| 0.2328 | 1.4723 | 2600 | 0.4593 | 0.3553 | |
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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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