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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-lv-60-espeak-cv-ft |
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tags: |
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- generated_from_trainer |
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datasets: |
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- voxpopuli |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-czech-colab-finetuned |
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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: voxpopuli |
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type: voxpopuli |
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config: cs |
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split: test |
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args: cs |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.6178421298458664 |
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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-large-xls-r-300m-czech-colab-finetuned |
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This model is a fine-tuned version of [facebook/wav2vec2-lv-60-espeak-cv-ft](https://huggingface.co/facebook/wav2vec2-lv-60-espeak-cv-ft) on the voxpopuli dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 624.5939 |
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- Wer: 0.6178 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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- num_epochs: 50 |
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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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| 3007.3212 | 3.51 | 100 | 1006.7374 | 0.9865 | |
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| 354.3011 | 7.02 | 200 | 563.6080 | 0.9980 | |
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| 211.5289 | 10.53 | 300 | 599.5796 | 0.9165 | |
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| 187.8653 | 14.04 | 400 | 447.1478 | 0.8099 | |
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| 163.1056 | 17.54 | 500 | 430.5204 | 0.6875 | |
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| 143.0342 | 21.05 | 600 | 413.8947 | 0.6850 | |
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| 116.0388 | 24.56 | 700 | 435.5743 | 0.6737 | |
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| 95.5554 | 28.07 | 800 | 490.6329 | 0.6339 | |
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| 80.6966 | 31.58 | 900 | 493.9658 | 0.6344 | |
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| 68.7335 | 35.09 | 1000 | 525.7507 | 0.6263 | |
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| 58.3269 | 38.6 | 1100 | 582.5747 | 0.6128 | |
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| 54.3181 | 42.11 | 1200 | 600.8087 | 0.6308 | |
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| 48.5287 | 45.61 | 1300 | 594.6959 | 0.6112 | |
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| 43.041 | 49.12 | 1400 | 624.5939 | 0.6178 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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