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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: 0.4349 |
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- Wer: 0.3391 |
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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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- training_steps: 2600 |
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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 | 0.0774 | 100 | 3.5346 | 1.0 | |
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| No log | 0.1549 | 200 | 2.9829 | 1.0 | |
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| No log | 0.2323 | 300 | 2.7705 | 1.0 | |
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| No log | 0.3097 | 400 | 1.3696 | 0.8535 | |
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| 3.7305 | 0.3871 | 500 | 1.0936 | 0.7465 | |
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| 3.7305 | 0.4646 | 600 | 0.8457 | 0.6413 | |
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| 3.7305 | 0.5420 | 700 | 0.7860 | 0.5836 | |
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| 3.7305 | 0.6194 | 800 | 0.7366 | 0.5637 | |
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| 3.7305 | 0.6969 | 900 | 0.7319 | 0.5494 | |
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| 0.7504 | 0.7743 | 1000 | 0.6439 | 0.5104 | |
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| 0.7504 | 0.8517 | 1100 | 0.6214 | 0.4759 | |
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| 0.7504 | 0.9292 | 1200 | 0.5957 | 0.4628 | |
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| 0.7504 | 1.0066 | 1300 | 0.5717 | 0.4353 | |
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| 0.7504 | 1.0840 | 1400 | 0.5500 | 0.4192 | |
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| 0.5571 | 1.1614 | 1500 | 0.5342 | 0.4073 | |
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| 0.5571 | 1.2389 | 1600 | 0.5207 | 0.4024 | |
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| 0.5571 | 1.3163 | 1700 | 0.5142 | 0.3969 | |
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| 0.5571 | 1.3937 | 1800 | 0.5083 | 0.3958 | |
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| 0.5571 | 1.4712 | 1900 | 0.4886 | 0.3825 | |
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| 0.4603 | 1.5486 | 2000 | 0.4733 | 0.3743 | |
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| 0.4603 | 1.6260 | 2100 | 0.4616 | 0.3619 | |
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| 0.4603 | 1.7034 | 2200 | 0.4536 | 0.3627 | |
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| 0.4603 | 1.7809 | 2300 | 0.4488 | 0.3487 | |
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| 0.4603 | 1.8583 | 2400 | 0.4429 | 0.3481 | |
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| 0.4163 | 1.9357 | 2500 | 0.4377 | 0.3419 | |
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| 0.4163 | 2.0132 | 2600 | 0.4349 | 0.3391 | |
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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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