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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-300m |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-E50_speed_pause |
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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-E50_speed_pause |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4049 |
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- Cer: 29.7227 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 3 |
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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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| 32.3933 | 0.1289 | 200 | 4.9500 | 100.0 | |
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| 4.8782 | 0.2579 | 400 | 4.6402 | 100.0 | |
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| 4.7485 | 0.3868 | 600 | 4.6460 | 100.0 | |
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| 4.7179 | 0.5158 | 800 | 4.5728 | 100.0 | |
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| 4.644 | 0.6447 | 1000 | 4.6080 | 99.0132 | |
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| 4.61 | 0.7737 | 1200 | 4.5600 | 98.2613 | |
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| 4.5722 | 0.9026 | 1400 | 4.5529 | 99.4537 | |
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| 4.4489 | 1.0316 | 1600 | 4.5026 | 98.1144 | |
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| 4.2793 | 1.1605 | 1800 | 4.1438 | 92.5928 | |
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| 3.6845 | 1.2895 | 2000 | 3.4651 | 61.3252 | |
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| 3.0089 | 1.4184 | 2200 | 2.6961 | 50.7049 | |
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| 2.6617 | 1.5474 | 2400 | 2.3715 | 46.2523 | |
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| 2.4745 | 1.6763 | 2600 | 2.2327 | 43.4739 | |
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| 2.2853 | 1.8053 | 2800 | 2.0575 | 41.7704 | |
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| 2.1079 | 1.9342 | 3000 | 1.9056 | 38.0639 | |
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| 1.9655 | 2.0632 | 3200 | 1.8005 | 35.8846 | |
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| 1.8115 | 2.1921 | 3400 | 1.6990 | 35.4088 | |
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| 1.7347 | 2.3211 | 3600 | 1.6111 | 33.3470 | |
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| 1.6653 | 2.4500 | 3800 | 1.5471 | 32.6833 | |
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| 1.5837 | 2.5790 | 4000 | 1.5360 | 31.9608 | |
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| 1.5514 | 2.7079 | 4200 | 1.4449 | 30.1398 | |
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| 1.4909 | 2.8369 | 4400 | 1.4166 | 29.7345 | |
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| 1.4908 | 2.9658 | 4600 | 1.4049 | 29.7227 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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