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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-large-xlsr-53 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: ierg4320_en_test |
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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: common_voice_13_0 |
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type: common_voice_13_0 |
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config: en |
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split: None |
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args: en |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.415272136474411 |
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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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# ierg4320_en_test |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9548 |
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- Wer: 0.4153 |
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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: 16 |
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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: 32 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 30 |
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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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| 5.0982 | 0.6211 | 400 | 2.9438 | 0.9938 | |
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| 1.7877 | 1.2422 | 800 | 1.0128 | 0.6645 | |
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| 0.8688 | 1.8634 | 1200 | 0.8012 | 0.5662 | |
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| 0.6808 | 2.4845 | 1600 | 0.8370 | 0.5366 | |
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| 0.6252 | 3.1056 | 2000 | 0.7710 | 0.5063 | |
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| 0.5532 | 3.7267 | 2400 | 0.7258 | 0.5041 | |
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| 0.5073 | 4.3478 | 2800 | 0.7337 | 0.4864 | |
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| 0.4834 | 4.9689 | 3200 | 0.7023 | 0.4777 | |
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| 0.4419 | 5.5901 | 3600 | 0.7542 | 0.4708 | |
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| 0.4326 | 6.2112 | 4000 | 0.7187 | 0.4647 | |
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| 0.4024 | 6.8323 | 4400 | 0.7212 | 0.4671 | |
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| 0.3809 | 7.4534 | 4800 | 0.7139 | 0.4582 | |
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| 0.3752 | 8.0745 | 5200 | 0.7296 | 0.4512 | |
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| 0.337 | 8.6957 | 5600 | 0.7207 | 0.4578 | |
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| 0.3305 | 9.3168 | 6000 | 0.7233 | 0.4528 | |
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| 0.3329 | 9.9379 | 6400 | 0.7178 | 0.4565 | |
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| 0.3047 | 10.5590 | 6800 | 0.7077 | 0.4518 | |
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| 0.2957 | 11.1801 | 7200 | 0.7788 | 0.4512 | |
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| 0.2913 | 11.8012 | 7600 | 0.7483 | 0.4528 | |
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| 0.2685 | 12.4224 | 8000 | 0.7644 | 0.4426 | |
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| 0.2666 | 13.0435 | 8400 | 0.7640 | 0.4427 | |
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| 0.2495 | 13.6646 | 8800 | 0.7959 | 0.4401 | |
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| 0.2501 | 14.2857 | 9200 | 0.7978 | 0.4494 | |
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| 0.2369 | 14.9068 | 9600 | 0.8217 | 0.4403 | |
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| 0.2282 | 15.5280 | 10000 | 0.8052 | 0.4359 | |
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| 0.2293 | 16.1491 | 10400 | 0.8688 | 0.4357 | |
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| 0.2165 | 16.7702 | 10800 | 0.8566 | 0.4385 | |
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| 0.2067 | 17.3913 | 11200 | 0.8504 | 0.4307 | |
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| 0.2034 | 18.0124 | 11600 | 0.8358 | 0.4346 | |
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| 0.1963 | 18.6335 | 12000 | 0.8729 | 0.4307 | |
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| 0.1846 | 19.2547 | 12400 | 0.8562 | 0.4349 | |
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| 0.189 | 19.8758 | 12800 | 0.8408 | 0.4266 | |
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| 0.1787 | 20.4969 | 13200 | 0.8424 | 0.4288 | |
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| 0.1757 | 21.1180 | 13600 | 0.8947 | 0.4327 | |
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| 0.1691 | 21.7391 | 14000 | 0.9070 | 0.4291 | |
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| 0.1652 | 22.3602 | 14400 | 0.8735 | 0.4299 | |
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| 0.1619 | 22.9814 | 14800 | 0.9224 | 0.4315 | |
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| 0.1544 | 23.6025 | 15200 | 0.9199 | 0.4278 | |
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| 0.1551 | 24.2236 | 15600 | 0.9089 | 0.4240 | |
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| 0.1449 | 24.8447 | 16000 | 0.9296 | 0.4229 | |
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| 0.1465 | 25.4658 | 16400 | 0.9476 | 0.4198 | |
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| 0.1434 | 26.0870 | 16800 | 0.9167 | 0.4193 | |
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| 0.1431 | 26.7081 | 17200 | 0.9492 | 0.4141 | |
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| 0.1335 | 27.3292 | 17600 | 0.9597 | 0.4185 | |
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| 0.1326 | 27.9503 | 18000 | 0.9516 | 0.4156 | |
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| 0.1333 | 28.5714 | 18400 | 0.9490 | 0.4153 | |
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| 0.1293 | 29.1925 | 18800 | 0.9605 | 0.4172 | |
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| 0.1257 | 29.8137 | 19200 | 0.9548 | 0.4153 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.5.1.post302 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.4 |
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