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--- |
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base_model: facebook/wav2vec2-xls-r-1b |
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library_name: transformers |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-1b-E10_freq_speed |
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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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# wav2vec2-1b-E10_freq_speed |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7340 |
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- Cer: 19.0026 |
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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: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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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: 50 |
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- num_epochs: 5 |
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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 | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:-------:| |
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| 11.3207 | 0.2580 | 200 | 3.4053 | 86.8891 | |
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| 1.8939 | 0.5160 | 400 | 1.8047 | 41.0303 | |
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| 1.1854 | 0.7741 | 600 | 1.4651 | 34.3691 | |
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| 0.9917 | 1.0321 | 800 | 1.0588 | 25.9516 | |
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| 0.744 | 1.2901 | 1000 | 1.1790 | 27.6962 | |
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| 0.6919 | 1.5481 | 1200 | 1.0604 | 25.9927 | |
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| 0.6347 | 1.8062 | 1400 | 0.9300 | 22.9323 | |
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| 0.5428 | 2.0642 | 1600 | 0.9996 | 24.9648 | |
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| 0.4724 | 2.3222 | 1800 | 0.9695 | 23.8252 | |
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| 0.4267 | 2.5802 | 2000 | 0.9463 | 23.7606 | |
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| 0.4096 | 2.8383 | 2200 | 0.8589 | 22.4448 | |
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| 0.3507 | 3.0963 | 2400 | 0.8145 | 20.7707 | |
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| 0.2874 | 3.3543 | 2600 | 0.8739 | 22.6856 | |
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| 0.2767 | 3.6123 | 2800 | 0.8657 | 21.8280 | |
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| 0.2663 | 3.8703 | 3000 | 0.8732 | 22.0630 | |
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| 0.2196 | 4.1284 | 3200 | 0.7671 | 19.4843 | |
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| 0.1867 | 4.3864 | 3400 | 0.7652 | 19.7016 | |
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| 0.1685 | 4.6444 | 3600 | 0.7288 | 18.7559 | |
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| 0.1677 | 4.9024 | 3800 | 0.7340 | 19.0026 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.3.1.post100 |
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- Datasets 2.19.1 |
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- Tokenizers 0.20.1 |
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