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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: WAVLM_TITML_IDN_model |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: audiofolder |
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type: audiofolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8181137724550899 |
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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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# WAVLM_TITML_IDN_model |
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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 audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7585 |
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- Accuracy: 0.8181 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 30 |
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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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| 8.0217 | 0.98 | 31 | 7.7416 | 0.0472 | |
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| 5.1076 | 2.0 | 63 | 3.5170 | 0.0472 | |
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| 3.0131 | 2.98 | 94 | 2.9921 | 0.0876 | |
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| 3.0119 | 4.0 | 126 | 2.9580 | 0.0928 | |
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| 2.685 | 4.98 | 157 | 2.6591 | 0.0793 | |
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| 2.4513 | 6.0 | 189 | 2.3831 | 0.1257 | |
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| 2.4415 | 6.98 | 220 | 2.3518 | 0.1415 | |
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| 2.2998 | 8.0 | 252 | 2.2327 | 0.1864 | |
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| 2.1987 | 8.98 | 283 | 2.1297 | 0.1549 | |
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| 2.1206 | 10.0 | 315 | 2.0529 | 0.2118 | |
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| 2.0542 | 10.98 | 346 | 1.9592 | 0.2507 | |
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| 1.9693 | 12.0 | 378 | 1.8652 | 0.2792 | |
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| 1.8677 | 12.98 | 409 | 1.7811 | 0.3668 | |
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| 1.7369 | 14.0 | 441 | 1.7902 | 0.2493 | |
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| 1.6551 | 14.98 | 472 | 1.6558 | 0.3406 | |
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| 1.6176 | 16.0 | 504 | 1.5724 | 0.3585 | |
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| 1.5666 | 16.98 | 535 | 1.5822 | 0.4207 | |
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| 1.5103 | 18.0 | 567 | 1.5028 | 0.4379 | |
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| 1.4695 | 18.98 | 598 | 1.4276 | 0.4970 | |
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| 1.3016 | 20.0 | 630 | 1.3621 | 0.4798 | |
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| 1.2025 | 20.98 | 661 | 1.2016 | 0.5778 | |
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| 1.1211 | 22.0 | 693 | 1.2346 | 0.5644 | |
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| 1.0204 | 22.98 | 724 | 1.0743 | 0.6445 | |
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| 0.9365 | 24.0 | 756 | 1.0121 | 0.6759 | |
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| 0.8553 | 24.98 | 787 | 0.9246 | 0.7290 | |
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| 0.7698 | 26.0 | 819 | 0.8603 | 0.7612 | |
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| 0.7336 | 26.98 | 850 | 0.8072 | 0.7867 | |
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| 0.6965 | 28.0 | 882 | 0.7770 | 0.8009 | |
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| 0.6662 | 28.98 | 913 | 0.7640 | 0.8136 | |
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| 0.63 | 29.52 | 930 | 0.7585 | 0.8181 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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