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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base-960h-fsc |
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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-base-960h-fsc |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0218 |
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- Accuracy: 0.9947 |
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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: 0.0005 |
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- train_batch_size: 48 |
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- eval_batch_size: 48 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 192 |
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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: 25 |
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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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| No log | 0.9959 | 120 | 0.3651 | 0.9380 | |
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| No log | 2.0 | 241 | 0.2352 | 0.9404 | |
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| No log | 2.9959 | 361 | 0.4245 | 0.8684 | |
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| No log | 4.0 | 482 | 0.0721 | 0.9837 | |
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| No log | 4.9959 | 602 | 0.0961 | 0.9768 | |
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| No log | 6.0 | 723 | 0.0632 | 0.9860 | |
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| No log | 6.9959 | 843 | 0.0498 | 0.9905 | |
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| No log | 8.0 | 964 | 0.0715 | 0.9834 | |
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| 0.4012 | 8.9959 | 1084 | 0.0907 | 0.9829 | |
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| 0.4012 | 10.0 | 1205 | 0.0644 | 0.9860 | |
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| 0.4012 | 10.9959 | 1325 | 0.0322 | 0.9921 | |
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| 0.4012 | 12.0 | 1446 | 0.0524 | 0.9881 | |
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| 0.4012 | 12.9959 | 1566 | 0.0450 | 0.9910 | |
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| 0.4012 | 14.0 | 1687 | 0.0227 | 0.9942 | |
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| 0.4012 | 14.9959 | 1807 | 0.0437 | 0.9908 | |
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| 0.4012 | 16.0 | 1928 | 0.0381 | 0.9924 | |
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| 0.1096 | 16.9959 | 2048 | 0.0218 | 0.9947 | |
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| 0.1096 | 18.0 | 2169 | 0.0300 | 0.9934 | |
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| 0.1096 | 18.9959 | 2289 | 0.0356 | 0.9931 | |
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| 0.1096 | 20.0 | 2410 | 0.0380 | 0.9937 | |
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| 0.1096 | 20.9959 | 2530 | 0.0417 | 0.9934 | |
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| 0.1096 | 22.0 | 2651 | 0.0268 | 0.9947 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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