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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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- minds14 |
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metrics: |
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- accuracy |
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model-index: |
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- name: my_awesome_lang_class_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: minds14 |
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type: minds14 |
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config: all |
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split: train |
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args: all |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.21236230110159118 |
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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_lang_class_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 minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3072 |
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- Accuracy: 0.2124 |
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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: 10 |
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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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| 2.597 | 1.0 | 51 | 2.5777 | 0.1481 | |
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| 2.4608 | 1.99 | 102 | 2.4484 | 0.1567 | |
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| 2.4352 | 2.99 | 153 | 2.4153 | 0.1548 | |
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| 2.3965 | 4.0 | 205 | 2.3796 | 0.1897 | |
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| 2.363 | 5.0 | 256 | 2.3622 | 0.1922 | |
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| 2.3369 | 5.99 | 307 | 2.3496 | 0.1854 | |
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| 2.292 | 6.99 | 358 | 2.3286 | 0.2038 | |
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| 2.2788 | 8.0 | 410 | 2.3170 | 0.2075 | |
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| 2.2537 | 9.0 | 461 | 2.3090 | 0.2044 | |
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| 2.241 | 9.95 | 510 | 2.3072 | 0.2124 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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