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--- |
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tags: |
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- automatic-speech-recognition |
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- abdusahmbzuai/arabic_speech_massive_300hrs |
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- generated_from_trainer |
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model-index: |
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- name: aradia-ctc-v1 |
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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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# aradia-ctc-v1 |
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This model is a fine-tuned version of [/l/users/abdulwahab.sahyoun/aradia/aradia-ctc-v1](https://huggingface.co//l/users/abdulwahab.sahyoun/aradia/aradia-ctc-v1) on the ABDUSAHMBZUAI/ARABIC_SPEECH_MASSIVE_300HRS - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7171 |
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- Wer: 0.3336 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 20.0 |
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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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| No log | 0.22 | 100 | 5.1889 | 1.0 | |
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| No log | 0.43 | 200 | 3.1129 | 1.0 | |
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| No log | 0.65 | 300 | 3.0503 | 1.0 | |
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| No log | 0.87 | 400 | 3.0279 | 1.0 | |
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| 6.2756 | 1.09 | 500 | 2.9965 | 1.0 | |
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| 6.2756 | 1.3 | 600 | 2.3618 | 0.9993 | |
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| 6.2756 | 1.52 | 700 | 1.2715 | 0.8758 | |
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| 6.2756 | 1.74 | 800 | 0.9971 | 0.7156 | |
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| 6.2756 | 1.96 | 900 | 0.8927 | 0.6382 | |
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| 1.712 | 2.17 | 1000 | 0.8252 | 0.5926 | |
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| 1.712 | 2.39 | 1100 | 0.7794 | 0.5434 | |
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| 1.712 | 2.61 | 1200 | 0.7557 | 0.5092 | |
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| 1.712 | 2.83 | 1300 | 0.7347 | 0.5203 | |
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| 1.712 | 3.04 | 1400 | 0.7189 | 0.4929 | |
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| 0.9305 | 3.26 | 1500 | 0.6820 | 0.4595 | |
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| 0.9305 | 3.48 | 1600 | 0.6792 | 0.4504 | |
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| 0.9305 | 3.69 | 1700 | 0.6596 | 0.4442 | |
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| 0.9305 | 3.91 | 1800 | 0.6756 | 0.4432 | |
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| 0.9305 | 4.13 | 1900 | 0.6663 | 0.4392 | |
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| 0.737 | 4.35 | 2000 | 0.6479 | 0.4372 | |
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| 0.737 | 4.56 | 2100 | 0.6353 | 0.4203 | |
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| 0.737 | 4.78 | 2200 | 0.6251 | 0.4088 | |
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| 0.737 | 5.0 | 2300 | 0.6209 | 0.4177 | |
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| 0.737 | 5.22 | 2400 | 0.6639 | 0.4094 | |
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| 0.6247 | 5.43 | 2500 | 0.6408 | 0.3970 | |
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| 0.6247 | 5.65 | 2600 | 0.6373 | 0.3932 | |
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| 0.6247 | 5.87 | 2700 | 0.6411 | 0.3928 | |
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| 0.6247 | 6.09 | 2800 | 0.6378 | 0.3897 | |
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| 0.6247 | 6.3 | 2900 | 0.6396 | 0.3929 | |
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| 0.5443 | 6.52 | 3000 | 0.6544 | 0.3864 | |
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| 0.5443 | 6.74 | 3100 | 0.6218 | 0.3786 | |
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| 0.5443 | 6.96 | 3200 | 0.6200 | 0.3784 | |
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| 0.5443 | 7.17 | 3300 | 0.6157 | 0.3791 | |
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| 0.5443 | 7.39 | 3400 | 0.6317 | 0.3798 | |
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| 0.4845 | 7.61 | 3500 | 0.6540 | 0.3771 | |
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| 0.4845 | 7.83 | 3600 | 0.6436 | 0.3670 | |
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| 0.4845 | 8.04 | 3700 | 0.6335 | 0.3695 | |
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| 0.4845 | 8.26 | 3800 | 0.6579 | 0.3610 | |
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| 0.4845 | 8.48 | 3900 | 0.6170 | 0.3613 | |
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| 0.4279 | 8.69 | 4000 | 0.6523 | 0.3617 | |
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| 0.4279 | 8.91 | 4100 | 0.6349 | 0.3577 | |
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| 0.4279 | 9.13 | 4200 | 0.6344 | 0.3673 | |
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| 0.4279 | 9.35 | 4300 | 0.6215 | 0.3641 | |
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| 0.4279 | 9.56 | 4400 | 0.6513 | 0.3608 | |
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| 0.3825 | 9.78 | 4500 | 0.6386 | 0.3605 | |
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| 0.3825 | 10.0 | 4600 | 0.6724 | 0.3549 | |
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| 0.3825 | 10.22 | 4700 | 0.6776 | 0.3602 | |
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| 0.3825 | 10.43 | 4800 | 0.6739 | 0.3544 | |
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| 0.3825 | 10.65 | 4900 | 0.6688 | 0.3557 | |
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| 0.3477 | 10.87 | 5000 | 0.6674 | 0.3564 | |
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| 0.3477 | 11.09 | 5100 | 0.6786 | 0.3476 | |
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| 0.3477 | 11.3 | 5200 | 0.6818 | 0.3478 | |
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| 0.3477 | 11.52 | 5300 | 0.6874 | 0.3470 | |
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| 0.3477 | 11.74 | 5400 | 0.6993 | 0.3424 | |
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| 0.3101 | 11.96 | 5500 | 0.6950 | 0.3404 | |
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| 0.3101 | 12.17 | 5600 | 0.6872 | 0.3406 | |
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| 0.3101 | 12.39 | 5700 | 0.6846 | 0.3424 | |
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| 0.3101 | 12.61 | 5800 | 0.7051 | 0.3405 | |
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| 0.3101 | 12.83 | 5900 | 0.7051 | 0.3378 | |
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| 0.2859 | 13.04 | 6000 | 0.6955 | 0.3403 | |
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| 0.2859 | 13.26 | 6100 | 0.7115 | 0.3390 | |
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| 0.2859 | 13.48 | 6200 | 0.7074 | 0.3384 | |
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| 0.2859 | 13.69 | 6300 | 0.7002 | 0.3376 | |
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| 0.2859 | 13.91 | 6400 | 0.7171 | 0.3360 | |
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| 0.2714 | 14.13 | 6500 | 0.7193 | 0.3341 | |
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| 0.2714 | 14.35 | 6600 | 0.7132 | 0.3347 | |
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| 0.2714 | 14.56 | 6700 | 0.7184 | 0.3353 | |
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| 0.2714 | 14.78 | 6800 | 0.7171 | 0.3331 | |
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### Framework versions |
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- Transformers 4.18.0.dev0 |
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- Pytorch 1.10.2+cu113 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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