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--- |
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language: |
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- pt |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_7_0 |
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- generated_from_trainer |
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- pt |
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datasets: |
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- mozilla-foundation/common_voice_7_0 |
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model-index: |
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- name: wavlm-large-CORAA-pt-cv7 |
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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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# wavlm-large-CORAA-pt-cv7 |
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This model is a fine-tuned version of [lgris/WavLM-large-CORAA-pt](https://huggingface.co/lgris/WavLM-large-CORAA-pt) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2546 |
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- Wer: 0.2261 |
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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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- gradient_accumulation_steps: 2 |
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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: 100 |
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- training_steps: 5000 |
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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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| 0.6029 | 0.13 | 100 | 0.3679 | 0.3347 | |
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| 0.5297 | 0.26 | 200 | 0.3516 | 0.3227 | |
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| 0.5134 | 0.39 | 300 | 0.3327 | 0.3167 | |
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| 0.4941 | 0.52 | 400 | 0.3281 | 0.3122 | |
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| 0.4816 | 0.65 | 500 | 0.3154 | 0.3102 | |
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| 0.4649 | 0.78 | 600 | 0.3199 | 0.3058 | |
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| 0.461 | 0.91 | 700 | 0.3047 | 0.2974 | |
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| 0.4613 | 1.04 | 800 | 0.3006 | 0.2900 | |
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| 0.4198 | 1.17 | 900 | 0.2951 | 0.2891 | |
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| 0.3864 | 1.3 | 1000 | 0.2989 | 0.2862 | |
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| 0.3963 | 1.43 | 1100 | 0.2932 | 0.2830 | |
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| 0.3953 | 1.56 | 1200 | 0.2936 | 0.2829 | |
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| 0.3962 | 1.69 | 1300 | 0.2952 | 0.2773 | |
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| 0.3811 | 1.82 | 1400 | 0.2915 | 0.2748 | |
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| 0.3736 | 1.95 | 1500 | 0.2839 | 0.2684 | |
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| 0.3507 | 2.08 | 1600 | 0.2914 | 0.2678 | |
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| 0.3277 | 2.21 | 1700 | 0.2895 | 0.2652 | |
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| 0.3344 | 2.34 | 1800 | 0.2843 | 0.2673 | |
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| 0.335 | 2.47 | 1900 | 0.2821 | 0.2635 | |
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| 0.3559 | 2.6 | 2000 | 0.2830 | 0.2599 | |
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| 0.3254 | 2.73 | 2100 | 0.2711 | 0.2577 | |
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| 0.3263 | 2.86 | 2200 | 0.2685 | 0.2546 | |
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| 0.3266 | 2.99 | 2300 | 0.2679 | 0.2521 | |
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| 0.3066 | 3.12 | 2400 | 0.2727 | 0.2526 | |
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| 0.2998 | 3.25 | 2500 | 0.2648 | 0.2537 | |
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| 0.2961 | 3.38 | 2600 | 0.2630 | 0.2519 | |
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| 0.3046 | 3.51 | 2700 | 0.2684 | 0.2506 | |
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| 0.3006 | 3.64 | 2800 | 0.2604 | 0.2492 | |
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| 0.2992 | 3.77 | 2900 | 0.2682 | 0.2508 | |
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| 0.2775 | 3.9 | 3000 | 0.2732 | 0.2440 | |
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| 0.2903 | 4.03 | 3100 | 0.2659 | 0.2427 | |
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| 0.2535 | 4.16 | 3200 | 0.2650 | 0.2433 | |
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| 0.2714 | 4.29 | 3300 | 0.2588 | 0.2394 | |
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| 0.2636 | 4.42 | 3400 | 0.2652 | 0.2434 | |
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| 0.2647 | 4.55 | 3500 | 0.2624 | 0.2371 | |
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| 0.2796 | 4.67 | 3600 | 0.2611 | 0.2373 | |
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| 0.2644 | 4.8 | 3700 | 0.2604 | 0.2341 | |
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| 0.2657 | 4.93 | 3800 | 0.2567 | 0.2331 | |
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| 0.2423 | 5.06 | 3900 | 0.2594 | 0.2322 | |
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| 0.2556 | 5.19 | 4000 | 0.2587 | 0.2323 | |
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| 0.2327 | 5.32 | 4100 | 0.2639 | 0.2299 | |
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| 0.2613 | 5.45 | 4200 | 0.2569 | 0.2310 | |
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| 0.2382 | 5.58 | 4300 | 0.2585 | 0.2298 | |
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| 0.2404 | 5.71 | 4400 | 0.2543 | 0.2287 | |
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| 0.2368 | 5.84 | 4500 | 0.2553 | 0.2286 | |
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| 0.2514 | 5.97 | 4600 | 0.2517 | 0.2279 | |
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| 0.2415 | 6.1 | 4700 | 0.2524 | 0.2270 | |
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| 0.2338 | 6.23 | 4800 | 0.2540 | 0.2265 | |
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| 0.219 | 6.36 | 4900 | 0.2549 | 0.2263 | |
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| 0.2428 | 6.49 | 5000 | 0.2546 | 0.2261 | |
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### Framework versions |
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- Transformers 4.16.1 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.2 |
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- Tokenizers 0.11.0 |
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