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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xlsr-53-ft-btb-ccv-cy |
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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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# wav2vec2-xlsr-53-ft-btb-ccv-cy |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4200 |
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- Wer: 0.3227 |
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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: 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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- training_steps: 2000 |
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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 | 0.1548 | 100 | 3.5623 | 1.0 | |
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| No log | 0.3096 | 200 | 3.2967 | 1.0 | |
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| No log | 0.4644 | 300 | 2.6484 | 1.0000 | |
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| No log | 0.6192 | 400 | 1.0602 | 0.7315 | |
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| 3.6398 | 0.7740 | 500 | 0.8942 | 0.6696 | |
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| 3.6398 | 0.9288 | 600 | 0.7116 | 0.5361 | |
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| 3.6398 | 1.0836 | 700 | 0.6648 | 0.5101 | |
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| 3.6398 | 1.2384 | 800 | 0.5869 | 0.4528 | |
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| 3.6398 | 1.3932 | 900 | 0.5698 | 0.4359 | |
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| 0.5976 | 1.5480 | 1000 | 0.5408 | 0.4112 | |
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| 0.5976 | 1.7028 | 1100 | 0.5229 | 0.4196 | |
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| 0.5976 | 1.8576 | 1200 | 0.5055 | 0.3955 | |
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| 0.5976 | 2.0124 | 1300 | 0.4808 | 0.3709 | |
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| 0.5976 | 2.1672 | 1400 | 0.4667 | 0.3580 | |
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| 0.443 | 2.3220 | 1500 | 0.4573 | 0.3582 | |
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| 0.443 | 2.4768 | 1600 | 0.4475 | 0.3452 | |
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| 0.443 | 2.6316 | 1700 | 0.4369 | 0.3478 | |
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| 0.443 | 2.7864 | 1800 | 0.4227 | 0.3298 | |
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| 0.443 | 2.9412 | 1900 | 0.4169 | 0.3271 | |
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| 0.3475 | 3.0960 | 2000 | 0.4200 | 0.3227 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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