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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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- nb_samtale |
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metrics: |
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- wer |
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model-index: |
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- name: cs2no_wav2vec2-large-xls-r-300m-czech-colab |
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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: nb_samtale |
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type: nb_samtale |
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config: annotations |
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split: test |
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args: annotations |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.8457142857142858 |
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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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# cs2no_wav2vec2-large-xls-r-300m-czech-colab |
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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 nb_samtale dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 396.8153 |
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- Wer: 0.8457 |
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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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| 3026.3663 | 3.51 | 100 | 472.1026 | 0.9873 | |
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| 336.2439 | 7.02 | 200 | 239.3806 | 0.9987 | |
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| 208.6184 | 10.53 | 300 | 206.7293 | 0.9917 | |
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| 182.6556 | 14.04 | 400 | 221.5585 | 0.8908 | |
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| 174.3151 | 17.54 | 500 | 262.3953 | 0.8921 | |
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| 140.57 | 21.05 | 600 | 225.9887 | 0.8330 | |
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| 114.5967 | 24.56 | 700 | 275.7823 | 0.8495 | |
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| 91.2748 | 28.07 | 800 | 314.0284 | 0.8610 | |
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| 80.0496 | 31.58 | 900 | 314.4608 | 0.8552 | |
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| 66.7338 | 35.09 | 1000 | 326.7965 | 0.8527 | |
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| 56.921 | 38.6 | 1100 | 373.0237 | 0.8425 | |
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| 50.7125 | 42.11 | 1200 | 374.9553 | 0.8527 | |
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| 47.4235 | 45.61 | 1300 | 404.8124 | 0.8489 | |
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| 45.1623 | 49.12 | 1400 | 396.8153 | 0.8457 | |
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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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