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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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- accuracy |
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base_model: facebook/wav2vec2-base |
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model-index: |
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- name: wav2vec2-base |
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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 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5735 |
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- Accuracy: 0.8913 |
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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: 50 |
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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 | 0.92 | 3 | 2.7459 | 0.1304 | |
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| No log | 1.85 | 6 | 2.6837 | 0.1087 | |
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| No log | 2.77 | 9 | 2.6583 | 0.1087 | |
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| 2.6599 | 4.0 | 13 | 2.6553 | 0.1087 | |
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| 2.6599 | 4.92 | 16 | 2.5628 | 0.1522 | |
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| 2.6599 | 5.85 | 19 | 2.4286 | 0.1739 | |
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| 2.3457 | 6.77 | 22 | 2.4705 | 0.1522 | |
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| 2.3457 | 8.0 | 26 | 2.2801 | 0.1522 | |
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| 2.3457 | 8.92 | 29 | 2.2110 | 0.2391 | |
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| 2.1136 | 9.85 | 32 | 2.1101 | 0.2391 | |
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| 2.1136 | 10.77 | 35 | 2.0434 | 0.3478 | |
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| 2.1136 | 12.0 | 39 | 2.2015 | 0.2609 | |
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| 1.8271 | 12.92 | 42 | 1.8463 | 0.2826 | |
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| 1.8271 | 13.85 | 45 | 1.8144 | 0.2391 | |
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| 1.8271 | 14.77 | 48 | 1.6712 | 0.2391 | |
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| 1.6517 | 16.0 | 52 | 1.6885 | 0.4348 | |
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| 1.6517 | 16.92 | 55 | 1.7268 | 0.4565 | |
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| 1.6517 | 17.85 | 58 | 1.5564 | 0.5435 | |
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| 1.5123 | 18.77 | 61 | 1.4261 | 0.5435 | |
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| 1.5123 | 20.0 | 65 | 1.2945 | 0.6739 | |
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| 1.5123 | 20.92 | 68 | 1.2329 | 0.6957 | |
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| 1.2441 | 21.85 | 71 | 1.1841 | 0.6957 | |
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| 1.2441 | 22.77 | 74 | 1.1297 | 0.7174 | |
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| 1.2441 | 24.0 | 78 | 1.0477 | 0.7826 | |
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| 1.0647 | 24.92 | 81 | 1.0039 | 0.7174 | |
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| 1.0647 | 25.85 | 84 | 0.9795 | 0.7174 | |
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| 1.0647 | 26.77 | 87 | 0.9619 | 0.7609 | |
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| 0.9374 | 28.0 | 91 | 0.8940 | 0.8043 | |
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| 0.9374 | 28.92 | 94 | 0.8675 | 0.8043 | |
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| 0.9374 | 29.85 | 97 | 0.8516 | 0.8043 | |
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| 0.7902 | 30.77 | 100 | 0.8203 | 0.8261 | |
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| 0.7902 | 32.0 | 104 | 0.7963 | 0.7609 | |
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| 0.7902 | 32.92 | 107 | 0.7329 | 0.8478 | |
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| 0.6959 | 33.85 | 110 | 0.7382 | 0.8043 | |
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| 0.6959 | 34.77 | 113 | 0.7205 | 0.8261 | |
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| 0.6959 | 36.0 | 117 | 0.6996 | 0.8043 | |
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| 0.6694 | 36.92 | 120 | 0.6949 | 0.8696 | |
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| 0.6694 | 37.85 | 123 | 0.7009 | 0.7826 | |
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| 0.6694 | 38.77 | 126 | 0.6502 | 0.8261 | |
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| 0.6226 | 40.0 | 130 | 0.5835 | 0.8478 | |
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| 0.6226 | 40.92 | 133 | 0.5735 | 0.8913 | |
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| 0.6226 | 41.85 | 136 | 0.5651 | 0.8913 | |
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| 0.6226 | 42.77 | 139 | 0.5624 | 0.8913 | |
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| 0.5746 | 44.0 | 143 | 0.5565 | 0.8913 | |
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| 0.5746 | 44.92 | 146 | 0.5476 | 0.8913 | |
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| 0.5746 | 45.85 | 149 | 0.5439 | 0.8913 | |
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| 0.5238 | 46.15 | 150 | 0.5435 | 0.8913 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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