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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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model-index: |
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- name: wav2vec2-1b-E50_speed2 |
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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-E50_speed2 |
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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: 0.7405 |
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- Cer: 24.6417 |
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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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| 26.7947 | 0.2580 | 200 | 30.8746 | 111.8127 | |
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| 7.993 | 0.5160 | 400 | 5.7855 | 94.2317 | |
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| 4.7455 | 0.7741 | 600 | 4.5989 | 93.9262 | |
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| 4.4924 | 1.0321 | 800 | 4.7152 | 93.2331 | |
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| 4.3711 | 1.2901 | 1000 | 4.7883 | 93.3564 | |
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| 4.3243 | 1.5481 | 1200 | 4.7205 | 92.4636 | |
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| 4.2683 | 1.8062 | 1400 | 4.5020 | 90.9305 | |
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| 4.1967 | 2.0642 | 1600 | 4.8431 | 92.8102 | |
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| 4.0612 | 2.3222 | 1800 | 4.8480 | 92.2697 | |
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| 3.6744 | 2.5802 | 2000 | 3.8378 | 77.9664 | |
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| 2.8934 | 2.8383 | 2200 | 2.9635 | 61.9713 | |
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| 2.1459 | 3.0963 | 2400 | 2.1180 | 51.9267 | |
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| 1.5896 | 3.3543 | 2600 | 1.5030 | 38.3870 | |
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| 1.0885 | 3.6123 | 2800 | 1.1457 | 30.6978 | |
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| 0.8797 | 3.8703 | 3000 | 0.9902 | 29.2234 | |
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| 0.7317 | 4.1284 | 3200 | 0.8634 | 25.7636 | |
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| 0.6046 | 4.3864 | 3400 | 0.7911 | 24.6476 | |
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| 0.5618 | 4.6444 | 3600 | 0.7773 | 25.6285 | |
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| 0.5027 | 4.9024 | 3800 | 0.7405 | 24.6417 | |
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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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