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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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- automatic-speech-recognition |
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- DewiBrynJones/banc-trawsgrifiadau-bangor-clean-with-ccv |
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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 the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-CLEAN-WITH-CCV - DEFAULT dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Wer: 1.0 |
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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: 8 |
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- eval_batch_size: 64 |
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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: 600 |
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- training_steps: 20000 |
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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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| 4.7126 | 0.0321 | 500 | 1.7047 | 0.9346 | |
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| 1.0533 | 0.0641 | 1000 | 1.1487 | 0.7907 | |
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| 0.8268 | 0.0962 | 1500 | 1.0602 | 0.7815 | |
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| 0.7188 | 0.1283 | 2000 | 0.9336 | 0.6717 | |
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| 0.6725 | 0.1603 | 2500 | 0.9304 | 0.6561 | |
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| 0.6295 | 0.1924 | 3000 | 0.8600 | 0.6257 | |
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| 0.6003 | 0.2244 | 3500 | 0.8395 | 0.6113 | |
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| 0.5847 | 0.2565 | 4000 | 0.7884 | 0.5861 | |
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| 0.5521 | 0.2886 | 4500 | 0.7741 | 0.5687 | |
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| 0.5477 | 0.3206 | 5000 | 0.7594 | 0.5536 | |
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| 0.5346 | 0.3527 | 5500 | 0.7482 | 0.5394 | |
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| 0.5154 | 0.3848 | 6000 | 0.7294 | 0.5352 | |
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| 0.492 | 0.4168 | 6500 | 0.7248 | 0.5493 | |
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| 0.4759 | 0.4489 | 7000 | 0.7077 | 0.5134 | |
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| 0.4655 | 0.4810 | 7500 | 0.6739 | 0.5064 | |
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| 0.4594 | 0.5130 | 8000 | 0.6575 | 0.5067 | |
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| 0.4538 | 0.5451 | 8500 | 0.6493 | 0.5003 | |
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| 0.4739 | 0.5771 | 9000 | 0.7677 | 0.5239 | |
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| 0.695 | 0.6092 | 9500 | nan | 1.0 | |
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| 0.0 | 0.6413 | 10000 | nan | 1.0 | |
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| 0.0 | 0.6733 | 10500 | nan | 1.0 | |
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| 0.0 | 0.7054 | 11000 | nan | 1.0 | |
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| 0.0 | 0.7375 | 11500 | nan | 1.0 | |
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| 0.0 | 0.7695 | 12000 | nan | 1.0 | |
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| 0.0 | 0.8016 | 12500 | nan | 1.0 | |
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| 0.0 | 0.8337 | 13000 | nan | 1.0 | |
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| 0.0 | 0.8657 | 13500 | nan | 1.0 | |
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| 0.0 | 0.8978 | 14000 | nan | 1.0 | |
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| 0.0 | 0.9298 | 14500 | nan | 1.0 | |
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| 0.0 | 0.9619 | 15000 | nan | 1.0 | |
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| 0.0 | 0.9940 | 15500 | nan | 1.0 | |
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| 0.0 | 1.0260 | 16000 | nan | 1.0 | |
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| 0.0 | 1.0581 | 16500 | nan | 1.0 | |
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| 0.0 | 1.0902 | 17000 | nan | 1.0 | |
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| 0.0 | 1.1222 | 17500 | nan | 1.0 | |
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| 0.0 | 1.1543 | 18000 | nan | 1.0 | |
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| 0.0 | 1.1864 | 18500 | nan | 1.0 | |
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| 0.0 | 1.2184 | 19000 | nan | 1.0 | |
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| 0.0 | 1.2505 | 19500 | nan | 1.0 | |
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| 0.0 | 1.2825 | 20000 | nan | 1.0 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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