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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-1b |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xls-r-1b-irish-5h-11k-steps |
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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: common_voice_17_0 |
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type: common_voice_17_0 |
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config: ga-IE |
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split: test |
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args: ga-IE |
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metrics: |
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- name: Wer |
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type: wer |
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value: 99.97108991037872 |
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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-xls-r-1b-irish-5h-11k-steps |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Wer: 99.9711 |
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- Cer: 99.9943 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 3000 |
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- training_steps: 11000 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
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| 2.9708 | 6.25 | 1000 | 2.8622 | 94.9986 | 93.1290 | |
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| 4.3506 | 12.5 | 2000 | 4.2474 | 96.5019 | 92.1035 | |
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| 4.4125 | 18.75 | 3000 | 4.2473 | 96.5019 | 92.2060 | |
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| 4.4092 | 25.0 | 4000 | 4.2474 | 96.3862 | 91.9781 | |
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| 4.436 | 31.25 | 5000 | 4.2474 | 96.4151 | 92.0978 | |
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| 4.4694 | 37.5 | 6000 | 4.2473 | 96.4441 | 92.1206 | |
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| 4.3806 | 43.75 | 7000 | 4.2474 | 96.3862 | 92.1775 | |
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| 4.4963 | 50.0 | 8000 | 4.2473 | 96.3862 | 92.0579 | |
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| 0.0 | 56.25 | 9000 | nan | 99.9711 | 99.9943 | |
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| 0.0 | 62.5 | 10000 | nan | 99.9711 | 99.9943 | |
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| 0.0 | 68.75 | 11000 | nan | 99.9711 | 99.9943 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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