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--- |
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library_name: transformers |
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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_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: en-US |
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split: train |
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args: en-US |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.07079646017699115 |
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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 minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6488 |
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- Accuracy: 0.0708 |
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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| No log | 0.8 | 3 | 2.6422 | 0.0973 | |
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| No log | 1.8 | 6 | 2.6472 | 0.0531 | |
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| No log | 2.8 | 9 | 2.6501 | 0.0531 | |
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| 12.1214 | 3.8 | 12 | 2.6439 | 0.0708 | |
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| 12.1214 | 4.8 | 15 | 2.6480 | 0.0354 | |
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| 12.1214 | 5.8 | 18 | 2.6473 | 0.0708 | |
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| 12.056 | 6.8 | 21 | 2.6484 | 0.0708 | |
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| 12.056 | 7.8 | 24 | 2.6490 | 0.0796 | |
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| 12.056 | 8.8 | 27 | 2.6492 | 0.0708 | |
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| 12.0168 | 9.8 | 30 | 2.6488 | 0.0708 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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