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--- |
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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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metrics: |
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- wer |
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model-index: |
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- name: Model_S_D_Wav2Vec2 |
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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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# Model_S_D_Wav2Vec2 |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0464 |
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- Wer: 0.2319 |
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- Cer: 0.0598 |
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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: 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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 3.5768 | 0.85 | 400 | 0.6152 | 0.5812 | 0.1905 | |
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| 0.3226 | 1.71 | 800 | 0.1026 | 0.3195 | 0.0722 | |
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| 0.1827 | 2.56 | 1200 | 0.0725 | 0.2048 | 0.0454 | |
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| 0.129 | 3.41 | 1600 | 0.0671 | 0.2393 | 0.0525 | |
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| 0.1075 | 4.26 | 2000 | 0.0556 | 0.2312 | 0.0497 | |
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| 0.0924 | 5.12 | 2400 | 0.0572 | 0.2040 | 0.0478 | |
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| 0.076 | 5.97 | 2800 | 0.0596 | 0.1472 | 0.0346 | |
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| 0.0695 | 6.82 | 3200 | 0.0608 | 0.2274 | 0.0510 | |
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| 0.0707 | 7.68 | 3600 | 0.0490 | 0.2665 | 0.0660 | |
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| 0.0597 | 8.53 | 4000 | 0.0509 | 0.2442 | 0.0593 | |
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| 0.0557 | 9.38 | 4400 | 0.0501 | 0.2533 | 0.0610 | |
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| 0.0503 | 10.23 | 4800 | 0.0519 | 0.2534 | 0.0622 | |
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| 0.0471 | 11.09 | 5200 | 0.0512 | 0.2585 | 0.0638 | |
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| 0.0417 | 11.94 | 5600 | 0.0497 | 0.2522 | 0.0610 | |
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| 0.0415 | 12.79 | 6000 | 0.0508 | 0.2547 | 0.0629 | |
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| 0.0372 | 13.65 | 6400 | 0.0497 | 0.2580 | 0.0643 | |
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| 0.0364 | 14.5 | 6800 | 0.0448 | 0.2498 | 0.0600 | |
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| 0.034 | 15.35 | 7200 | 0.0522 | 0.2419 | 0.0593 | |
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| 0.0306 | 16.2 | 7600 | 0.0510 | 0.2433 | 0.0560 | |
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| 0.0345 | 17.06 | 8000 | 0.0503 | 0.2610 | 0.0657 | |
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| 0.0266 | 17.91 | 8400 | 0.0462 | 0.2434 | 0.0620 | |
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| 0.0273 | 18.76 | 8800 | 0.0507 | 0.2456 | 0.0622 | |
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| 0.0216 | 19.62 | 9200 | 0.0466 | 0.2214 | 0.0531 | |
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| 0.0208 | 20.47 | 9600 | 0.0497 | 0.2396 | 0.0598 | |
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| 0.0201 | 21.32 | 10000 | 0.0470 | 0.2332 | 0.0559 | |
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| 0.0174 | 22.17 | 10400 | 0.0418 | 0.2346 | 0.0590 | |
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| 0.0198 | 23.03 | 10800 | 0.0472 | 0.2386 | 0.0602 | |
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| 0.0149 | 23.88 | 11200 | 0.0490 | 0.2446 | 0.0638 | |
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| 0.0133 | 24.73 | 11600 | 0.0497 | 0.2430 | 0.0632 | |
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| 0.0118 | 25.59 | 12000 | 0.0498 | 0.2368 | 0.0620 | |
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| 0.0106 | 26.44 | 12400 | 0.0453 | 0.2309 | 0.0590 | |
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| 0.0104 | 27.29 | 12800 | 0.0452 | 0.2296 | 0.0583 | |
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| 0.0085 | 28.14 | 13200 | 0.0467 | 0.2352 | 0.0604 | |
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| 0.0081 | 29.0 | 13600 | 0.0470 | 0.2310 | 0.0592 | |
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| 0.0079 | 29.85 | 14000 | 0.0464 | 0.2319 | 0.0598 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 1.18.3 |
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- Tokenizers 0.13.3 |
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