| --- |
| library_name: transformers |
| license: cc-by-nc-sa-4.0 |
| base_model: fav-kky/wav2vec2-base-cs-80k-ClTRUS |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: wav2vec2-ctc |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # wav2vec2-ctc |
|
|
| This model is a fine-tuned version of [fav-kky/wav2vec2-base-cs-80k-ClTRUS](https://huggingface.co/fav-kky/wav2vec2-base-cs-80k-ClTRUS) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5716 |
| - Wer: 0.9831 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.3 |
| - num_epochs: 60 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-------:|:-----:|:---------------:|:------:| |
| | 3.4027 | 2.1942 | 2000 | 3.5478 | 1.0 | |
| | 3.2864 | 4.3884 | 4000 | 3.4339 | 1.0 | |
| | 2.8505 | 6.5826 | 6000 | 2.8626 | 0.9998 | |
| | 2.5028 | 8.7767 | 8000 | 2.5475 | 0.9989 | |
| | 2.2853 | 10.9709 | 10000 | 2.3584 | 0.9989 | |
| | 2.1248 | 13.1651 | 12000 | 2.2147 | 0.9992 | |
| | 2.0013 | 15.3593 | 14000 | 2.1026 | 0.9989 | |
| | 1.8839 | 17.5535 | 16000 | 1.9910 | 0.9986 | |
| | 1.7885 | 19.7477 | 18000 | 1.9146 | 0.9991 | |
| | 1.7114 | 21.9419 | 20000 | 1.8460 | 0.9977 | |
| | 1.6532 | 24.1360 | 22000 | 1.7951 | 0.9968 | |
| | 1.606 | 26.3302 | 24000 | 1.7419 | 0.9959 | |
| | 1.5582 | 28.5244 | 26000 | 1.7155 | 0.9958 | |
| | 1.5257 | 30.7186 | 28000 | 1.6877 | 0.9917 | |
| | 1.4951 | 32.9128 | 30000 | 1.6671 | 0.9923 | |
| | 1.4748 | 35.1070 | 32000 | 1.6511 | 0.9902 | |
| | 1.4454 | 37.3012 | 34000 | 1.6320 | 0.9891 | |
| | 1.4241 | 39.4953 | 36000 | 1.6238 | 0.9884 | |
| | 1.4038 | 41.6895 | 38000 | 1.6056 | 0.9843 | |
| | 1.3902 | 43.8837 | 40000 | 1.5955 | 0.9839 | |
| | 1.3795 | 46.0779 | 42000 | 1.5908 | 0.9848 | |
| | 1.3708 | 48.2721 | 44000 | 1.5855 | 0.9833 | |
| | 1.3633 | 50.4663 | 46000 | 1.5863 | 0.9858 | |
| | 1.3564 | 52.6604 | 48000 | 1.5791 | 0.9830 | |
| | 1.3542 | 54.8546 | 50000 | 1.5714 | 0.9818 | |
| | 1.3379 | 57.0488 | 52000 | 1.5722 | 0.9824 | |
| | 1.3441 | 59.2430 | 54000 | 1.5716 | 0.9831 | |
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| ### Framework versions |
|
|
| - Transformers 4.45.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
|
|
