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wav2vec2-xls-r-300m-tr

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
wav2vec2
mozilla-foundation/common_voice_11_0
Generated from Trainer
Eval Results
Inference Endpoints
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_11_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-xls-r-300m-tr
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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_11_0
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+ type: common_voice_11_0
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+ config: tr
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+ split: test
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+ args: tr
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.28665152662124654
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+ ---
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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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+
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+ # wav2vec2-xls-r-300m-tr
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+
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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 common_voice_11_0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3184
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+ - Wer: 0.2867
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+ - Cer: 0.0681
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 64
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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: 500
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+ - num_epochs: 30.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
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+ | No log | 0.71 | 400 | 1.7290 | 0.9804 | 0.4797 |
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+ | 4.5435 | 1.42 | 800 | 0.4810 | 0.5774 | 0.1450 |
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+ | 0.523 | 2.12 | 1200 | 0.3859 | 0.4812 | 0.1156 |
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+ | 0.3449 | 2.83 | 1600 | 0.3492 | 0.4498 | 0.1095 |
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+ | 0.2814 | 3.54 | 2000 | 0.3660 | 0.4466 | 0.1099 |
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+ | 0.2814 | 4.25 | 2400 | 0.3766 | 0.4235 | 0.1043 |
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+ | 0.2463 | 4.96 | 2800 | 0.3416 | 0.4119 | 0.1010 |
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+ | 0.2296 | 5.66 | 3200 | 0.3322 | 0.4013 | 0.0979 |
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+ | 0.2143 | 6.37 | 3600 | 0.3370 | 0.3956 | 0.0972 |
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+ | 0.1955 | 7.08 | 4000 | 0.3401 | 0.4033 | 0.0998 |
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+ | 0.1955 | 7.79 | 4400 | 0.3375 | 0.3889 | 0.0962 |
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+ | 0.1845 | 8.5 | 4800 | 0.3455 | 0.3752 | 0.0923 |
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+ | 0.1752 | 9.2 | 5200 | 0.3336 | 0.3718 | 0.0925 |
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+ | 0.1705 | 9.91 | 5600 | 0.3145 | 0.3653 | 0.0892 |
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+ | 0.1585 | 10.62 | 6000 | 0.3410 | 0.3737 | 0.0922 |
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+ | 0.1585 | 11.33 | 6400 | 0.3296 | 0.3664 | 0.0899 |
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+ | 0.1474 | 12.04 | 6800 | 0.3492 | 0.3590 | 0.0899 |
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+ | 0.1485 | 12.74 | 7200 | 0.3176 | 0.3506 | 0.0867 |
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+ | 0.137 | 13.45 | 7600 | 0.3532 | 0.3600 | 0.0890 |
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+ | 0.1291 | 14.16 | 8000 | 0.3318 | 0.3571 | 0.0873 |
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+ | 0.1291 | 14.87 | 8400 | 0.3353 | 0.3548 | 0.0883 |
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+ | 0.1274 | 15.58 | 8800 | 0.3235 | 0.3396 | 0.0823 |
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+ | 0.1198 | 16.28 | 9200 | 0.3259 | 0.3389 | 0.0832 |
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+ | 0.1164 | 16.99 | 9600 | 0.3263 | 0.3411 | 0.0844 |
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+ | 0.1119 | 17.7 | 10000 | 0.3254 | 0.3377 | 0.0824 |
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+ | 0.1119 | 18.41 | 10400 | 0.3243 | 0.3331 | 0.0812 |
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+ | 0.1054 | 19.12 | 10800 | 0.3223 | 0.3239 | 0.0790 |
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+ | 0.1017 | 19.82 | 11200 | 0.3054 | 0.3190 | 0.0774 |
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+ | 0.0964 | 20.53 | 11600 | 0.3278 | 0.3237 | 0.0785 |
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+ | 0.0903 | 21.24 | 12000 | 0.3167 | 0.3177 | 0.0774 |
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+ | 0.0903 | 21.95 | 12400 | 0.3331 | 0.3124 | 0.0766 |
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+ | 0.0886 | 22.65 | 12800 | 0.3099 | 0.3089 | 0.0745 |
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+ | 0.0836 | 23.36 | 13200 | 0.3171 | 0.3048 | 0.0731 |
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+ | 0.0796 | 24.07 | 13600 | 0.3158 | 0.3041 | 0.0733 |
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+ | 0.0739 | 24.78 | 14000 | 0.3203 | 0.3003 | 0.0721 |
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+ | 0.0739 | 25.49 | 14400 | 0.3138 | 0.2974 | 0.0713 |
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+ | 0.0742 | 26.19 | 14800 | 0.3197 | 0.2959 | 0.0711 |
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+ | 0.07 | 26.9 | 15200 | 0.3232 | 0.2952 | 0.0703 |
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+ | 0.0654 | 27.61 | 15600 | 0.3243 | 0.2939 | 0.0701 |
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+ | 0.0631 | 28.32 | 16000 | 0.3213 | 0.2876 | 0.0688 |
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+ | 0.0631 | 29.03 | 16400 | 0.3151 | 0.2880 | 0.0685 |
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+ | 0.0607 | 29.73 | 16800 | 0.3184 | 0.2867 | 0.0681 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.0.dev0
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+ - Pytorch 1.13.1+cu117
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+ - Datasets 2.8.1.dev0
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+ - Tokenizers 0.13.2