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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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model-index: |
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name: wav2vec2-base-libir-zenodo |
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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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# wav2vec2-base-libir-zenodo |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4238 |
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- Wer: 0.4336 |
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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: 1e-05 |
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- train_batch_size: 2 |
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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: 1000 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 3.053 | 1.0 | 31 | 3.1494 | 0.7345 | |
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| 2.9742 | 2.0 | 62 | 3.0527 | 0.7257 | |
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| 2.9139 | 3.0 | 93 | 2.8808 | 0.7257 | |
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| 2.6586 | 4.0 | 124 | 2.6648 | 0.6726 | |
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| 2.7117 | 5.0 | 155 | 2.4695 | 0.6372 | |
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| 2.5173 | 6.0 | 186 | 2.3087 | 0.6195 | |
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| 2.3665 | 7.0 | 217 | 2.2745 | 0.6018 | |
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| 2.1276 | 8.0 | 248 | 2.2180 | 0.5752 | |
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| 2.1624 | 9.0 | 279 | 2.1311 | 0.5752 | |
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| 2.0312 | 10.0 | 310 | 2.0358 | 0.5575 | |
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| 2.0652 | 11.0 | 341 | 1.9146 | 0.5310 | |
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| 1.7963 | 12.0 | 372 | 1.8346 | 0.5221 | |
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| 1.6811 | 13.0 | 403 | 1.8351 | 0.5398 | |
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| 1.5929 | 14.0 | 434 | 1.8256 | 0.4779 | |
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| 1.6644 | 15.0 | 465 | 1.7572 | 0.4779 | |
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| 1.5411 | 16.0 | 496 | 1.8740 | 0.4779 | |
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| 1.4027 | 17.0 | 527 | 1.5143 | 0.4779 | |
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| 1.2634 | 18.0 | 558 | 1.3864 | 0.4867 | |
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| 1.1053 | 19.0 | 589 | 1.3192 | 0.4425 | |
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| 1.0517 | 20.0 | 620 | 1.4705 | 0.4602 | |
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| 1.1033 | 21.0 | 651 | 1.6006 | 0.4956 | |
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| 0.9992 | 22.0 | 682 | 1.4748 | 0.5044 | |
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| 0.8987 | 23.0 | 713 | 1.3544 | 0.4867 | |
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| 0.9656 | 24.0 | 744 | 1.2673 | 0.4336 | |
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| 0.952 | 25.0 | 775 | 1.3955 | 0.4071 | |
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| 0.8507 | 26.0 | 806 | 1.3520 | 0.4425 | |
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| 0.8269 | 27.0 | 837 | 1.8992 | 0.4336 | |
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| 0.7255 | 28.0 | 868 | 1.9850 | 0.4425 | |
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| 0.8269 | 29.0 | 899 | 3.0089 | 0.4425 | |
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| 0.6178 | 30.0 | 930 | 1.4238 | 0.4336 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.13.3 |
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- Tokenizers 0.10.3 |
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