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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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: my_awesome_mind_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: test |
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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: 0.2793103448275862 |
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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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# my_awesome_mind_model |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3078 |
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- Accuracy: 0.2793 |
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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: 3e-05 |
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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 | 0.73 | 2 | 2.6832 | 0.1241 | |
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| No log | 1.82 | 5 | 2.6800 | 0.1103 | |
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| No log | 2.91 | 8 | 2.6726 | 0.1207 | |
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| 2.6498 | 4.0 | 11 | 2.6580 | 0.1483 | |
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| 2.6498 | 4.73 | 13 | 2.6454 | 0.1379 | |
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| 2.6498 | 5.82 | 16 | 2.6245 | 0.1379 | |
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| 2.6498 | 6.91 | 19 | 2.6038 | 0.1414 | |
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| 2.6057 | 8.0 | 22 | 2.5839 | 0.1552 | |
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| 2.6057 | 8.73 | 24 | 2.5656 | 0.1655 | |
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| 2.6057 | 9.82 | 27 | 2.5378 | 0.1552 | |
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| 2.524 | 10.91 | 30 | 2.5192 | 0.1862 | |
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| 2.524 | 12.0 | 33 | 2.4996 | 0.1931 | |
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| 2.524 | 12.73 | 35 | 2.4900 | 0.2069 | |
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| 2.524 | 13.82 | 38 | 2.4663 | 0.2138 | |
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| 2.4304 | 14.91 | 41 | 2.4498 | 0.2207 | |
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| 2.4304 | 16.0 | 44 | 2.4309 | 0.2138 | |
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| 2.4304 | 16.73 | 46 | 2.4291 | 0.2310 | |
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| 2.4304 | 17.82 | 49 | 2.4106 | 0.2517 | |
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| 2.3519 | 18.91 | 52 | 2.3944 | 0.2310 | |
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| 2.3519 | 20.0 | 55 | 2.3949 | 0.2414 | |
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| 2.3519 | 20.73 | 57 | 2.3807 | 0.2414 | |
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| 2.2774 | 21.82 | 60 | 2.3661 | 0.2379 | |
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| 2.2774 | 22.91 | 63 | 2.3600 | 0.2345 | |
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| 2.2774 | 24.0 | 66 | 2.3572 | 0.2483 | |
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| 2.2774 | 24.73 | 68 | 2.3430 | 0.2345 | |
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| 2.2402 | 25.82 | 71 | 2.3369 | 0.2586 | |
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| 2.2402 | 26.91 | 74 | 2.3365 | 0.2586 | |
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| 2.2402 | 28.0 | 77 | 2.3301 | 0.2621 | |
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| 2.2402 | 28.73 | 79 | 2.3274 | 0.2724 | |
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| 2.1901 | 29.82 | 82 | 2.3266 | 0.2759 | |
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| 2.1901 | 30.91 | 85 | 2.3207 | 0.2655 | |
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| 2.1901 | 32.0 | 88 | 2.3115 | 0.2724 | |
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| 2.148 | 32.73 | 90 | 2.3084 | 0.2724 | |
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| 2.148 | 33.82 | 93 | 2.3082 | 0.2724 | |
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| 2.148 | 34.91 | 96 | 2.3094 | 0.2828 | |
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| 2.148 | 36.0 | 99 | 2.3080 | 0.2793 | |
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| 2.1303 | 36.36 | 100 | 2.3078 | 0.2793 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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