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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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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: xls-r-300-cv17-bulgarian-adap-ru |
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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_17_0 |
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type: common_voice_17_0 |
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config: bg |
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split: validation |
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args: bg |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3023246994576965 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/badr-nlp/xlsr-continual-finetuning-polish/runs/hevbjmzy) |
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# xls-r-300-cv17-bulgarian-adap-ru |
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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_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3977 |
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- Wer: 0.3023 |
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- Cer: 0.0722 |
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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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- mixed_precision_training: Native AMP |
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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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| 3.1617 | 0.6579 | 100 | 3.1554 | 1.0 | 1.0 | |
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| 1.0032 | 1.3158 | 200 | 1.0726 | 0.8684 | 0.2419 | |
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| 0.5552 | 1.9737 | 300 | 0.4924 | 0.5297 | 0.1303 | |
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| 0.2763 | 2.6316 | 400 | 0.3795 | 0.4442 | 0.1043 | |
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| 0.2273 | 3.2895 | 500 | 0.3769 | 0.4222 | 0.1014 | |
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| 0.3216 | 3.9474 | 600 | 0.3611 | 0.3993 | 0.0971 | |
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| 0.1553 | 4.6053 | 700 | 0.3566 | 0.3927 | 0.0936 | |
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| 0.1414 | 5.2632 | 800 | 0.3676 | 0.3869 | 0.0923 | |
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| 0.1774 | 5.9211 | 900 | 0.3680 | 0.3758 | 0.0901 | |
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| 0.1256 | 6.5789 | 1000 | 0.3637 | 0.3775 | 0.0916 | |
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| 0.2416 | 7.2368 | 1100 | 0.3893 | 0.3963 | 0.0951 | |
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| 0.1213 | 7.8947 | 1200 | 0.3677 | 0.3596 | 0.0864 | |
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| 0.0911 | 8.5526 | 1300 | 0.3850 | 0.3739 | 0.0891 | |
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| 0.0859 | 9.2105 | 1400 | 0.3962 | 0.3658 | 0.0883 | |
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| 0.0998 | 9.8684 | 1500 | 0.3608 | 0.3530 | 0.0846 | |
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| 0.108 | 10.5263 | 1600 | 0.3932 | 0.3908 | 0.0920 | |
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| 0.0824 | 11.1842 | 1700 | 0.4147 | 0.3591 | 0.0870 | |
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| 0.0888 | 11.8421 | 1800 | 0.4040 | 0.3660 | 0.0878 | |
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| 0.0609 | 12.5 | 1900 | 0.4097 | 0.3542 | 0.0857 | |
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| 0.0692 | 13.1579 | 2000 | 0.4127 | 0.3639 | 0.0874 | |
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| 0.0513 | 13.8158 | 2100 | 0.4118 | 0.3560 | 0.0870 | |
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| 0.0752 | 14.4737 | 2200 | 0.4044 | 0.3591 | 0.0888 | |
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| 0.0833 | 15.1316 | 2300 | 0.3956 | 0.3374 | 0.0812 | |
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| 0.0826 | 15.7895 | 2400 | 0.3953 | 0.3356 | 0.0811 | |
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| 0.0934 | 16.4474 | 2500 | 0.4053 | 0.3394 | 0.0819 | |
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| 0.0562 | 17.1053 | 2600 | 0.4243 | 0.3534 | 0.0843 | |
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| 0.0661 | 17.7632 | 2700 | 0.4021 | 0.3340 | 0.0791 | |
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| 0.0496 | 18.4211 | 2800 | 0.4052 | 0.3387 | 0.0818 | |
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| 0.0599 | 19.0789 | 2900 | 0.4101 | 0.3385 | 0.0806 | |
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| 0.0446 | 19.7368 | 3000 | 0.3990 | 0.3362 | 0.0810 | |
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| 0.0482 | 20.3947 | 3100 | 0.4077 | 0.3274 | 0.0781 | |
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| 0.0309 | 21.0526 | 3200 | 0.4343 | 0.3397 | 0.0817 | |
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| 0.0757 | 21.7105 | 3300 | 0.4154 | 0.3252 | 0.0781 | |
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| 0.0377 | 22.3684 | 3400 | 0.4273 | 0.3206 | 0.0770 | |
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| 0.0282 | 23.0263 | 3500 | 0.3998 | 0.3159 | 0.0751 | |
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| 0.0676 | 23.6842 | 3600 | 0.3960 | 0.3111 | 0.0745 | |
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| 0.0673 | 24.3421 | 3700 | 0.3997 | 0.3100 | 0.0741 | |
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| 0.1793 | 25.0 | 3800 | 0.4065 | 0.3106 | 0.0738 | |
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| 0.0572 | 25.6579 | 3900 | 0.3951 | 0.3098 | 0.0739 | |
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| 0.0208 | 26.3158 | 4000 | 0.4097 | 0.3106 | 0.0740 | |
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| 0.0562 | 26.9737 | 4100 | 0.4016 | 0.3081 | 0.0734 | |
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| 0.0314 | 27.6316 | 4200 | 0.3939 | 0.3008 | 0.0715 | |
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| 0.0235 | 28.2895 | 4300 | 0.4008 | 0.3023 | 0.0720 | |
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| 0.0443 | 28.9474 | 4400 | 0.3963 | 0.3033 | 0.0724 | |
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| 0.027 | 29.6053 | 4500 | 0.3977 | 0.3023 | 0.0722 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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