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--- |
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pipeline_tag: audio-classification |
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datasets: |
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- common_language |
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--- |
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# Language Classification |
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A model trained for language classification. Thanks to @sanchit-gandhi for [this code](https://huggingface.co/sanchit-gandhi/whisper-base-ft-common-language-id) which was used to train the model. |
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This model was trained for 15 epochs. |
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## Evaluation |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1229 |
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- Accuracy: 0.7401 |
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## 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: 64 |
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- eval_batch_size: 16 |
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- seed: 0 |
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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_ratio: 0.1 |
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- num_epochs: 15.0 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 3.1638 | 1.0 | 347 | 3.0152 | 0.4200 | |
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| 2.0788 | 2.0 | 694 | 1.9700 | 0.5504 | |
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| 1.4236 | 3.0 | 1041 | 1.5048 | 0.6374 | |
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| 1.0305 | 4.0 | 1388 | 1.2979 | 0.6685 | |
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| 0.7651 | 5.0 | 1735 | 1.1692 | 0.7023 | |
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| 0.5782 | 6.0 | 2082 | 1.0896 | 0.7227 | |
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| 0.4483 | 7.0 | 2429 | 1.0605 | 0.7198 | |
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| 0.3253 | 8.0 | 2776 | 1.0255 | 0.7376 | |
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| 0.2589 | 9.0 | 3123 | 1.0478 | 0.7354 | |
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| 0.1825 | 10.0 | 3470 | 1.0677 | 0.7318 | |
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| 0.1489 | 11.0 | 3817 | 1.0946 | 0.7373 | |
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| 0.1274 | 12.0 | 4164 | 1.1180 | 0.7376 | |
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| 0.1074 | 13.0 | 4511 | 1.1229 | 0.7401 | |
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| 0.0979 | 14.0 | 4858 | 1.1523 | 0.7383 | |
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| 0.0914 | 15.0 | 5205 | 1.1498 | 0.7401 | |
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## Disclaimer |
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THE MODEL IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS MODEL INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS MODEL. |
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