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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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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-Irish-common-voice-Fleurs-living-audio-300m |
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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-Irish-common-voice-Fleurs-living-audio-300m |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3362 |
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- Wer: 0.1978 |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 24 |
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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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- num_epochs: 18.0 |
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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 | 0.56 | 200 | 2.8832 | 1.0 | |
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| No log | 1.11 | 400 | 1.1705 | 0.7788 | |
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| 3.3987 | 1.67 | 600 | 0.7739 | 0.5895 | |
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| 3.3987 | 2.23 | 800 | 0.6045 | 0.4902 | |
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| 0.8313 | 2.78 | 1000 | 0.5235 | 0.4394 | |
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| 0.8313 | 3.34 | 1200 | 0.4824 | 0.4002 | |
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| 0.8313 | 3.9 | 1400 | 0.4378 | 0.3754 | |
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| 0.5342 | 4.46 | 1600 | 0.4433 | 0.3634 | |
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| 0.5342 | 5.01 | 1800 | 0.4103 | 0.3485 | |
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| 0.3792 | 5.57 | 2000 | 0.3816 | 0.3310 | |
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| 0.3792 | 6.13 | 2200 | 0.3953 | 0.3225 | |
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| 0.3792 | 6.68 | 2400 | 0.3995 | 0.3132 | |
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| 0.2924 | 7.24 | 2600 | 0.3907 | 0.2930 | |
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| 0.2924 | 7.8 | 2800 | 0.3517 | 0.2740 | |
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| 0.2217 | 8.36 | 3000 | 0.3361 | 0.2591 | |
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| 0.2217 | 8.91 | 3200 | 0.3340 | 0.2451 | |
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| 0.2217 | 9.47 | 3400 | 0.3126 | 0.2448 | |
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| 0.1714 | 10.03 | 3600 | 0.3441 | 0.2556 | |
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| 0.1714 | 10.58 | 3800 | 0.3404 | 0.2521 | |
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| 0.1395 | 11.14 | 4000 | 0.3728 | 0.2518 | |
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| 0.1395 | 11.7 | 4200 | 0.3829 | 0.2396 | |
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| 0.1395 | 12.26 | 4400 | 0.3466 | 0.2361 | |
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| 0.1069 | 12.81 | 4600 | 0.3188 | 0.2241 | |
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| 0.1069 | 13.37 | 4800 | 0.3396 | 0.2197 | |
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| 0.0845 | 13.93 | 5000 | 0.3365 | 0.2206 | |
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| 0.0845 | 14.48 | 5200 | 0.3459 | 0.2209 | |
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| 0.0845 | 15.04 | 5400 | 0.3429 | 0.2194 | |
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| 0.0675 | 15.6 | 5600 | 0.3434 | 0.2182 | |
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| 0.0675 | 16.16 | 5800 | 0.3434 | 0.2083 | |
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| 0.0561 | 16.71 | 6000 | 0.3375 | 0.2036 | |
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| 0.0561 | 17.27 | 6200 | 0.3446 | 0.1987 | |
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| 0.0561 | 17.83 | 6400 | 0.3362 | 0.1978 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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