End of training
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README.md
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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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metrics:
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- accuracy
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model-index:
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- name: Audioclasswindows
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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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# Audioclasswindows
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on
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It achieves the following results on the evaluation set:
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- Loss: 2.
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- Accuracy: 0.0796
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size:
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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:
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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.
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| 2.
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| 2.6363 | 4.8 | 18 | 2.6579 | 0.0885 |
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| 2.6244 | 5.87 | 22 | 2.6587 | 0.0885 |
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| 2.6244 | 6.93 | 26 | 2.6608 | 0.0885 |
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| 2.6103 | 8.0 | 30 | 2.6632 | 0.0796 |
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| 2.6103 | 8.8 | 33 | 2.6664 | 0.0796 |
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| 2.6103 | 9.87 | 37 | 2.6692 | 0.0796 |
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| 2.6019 | 10.93 | 41 | 2.6722 | 0.0796 |
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| 2.6019 | 12.0 | 45 | 2.6740 | 0.0796 |
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| 2.6019 | 12.8 | 48 | 2.6744 | 0.0796 |
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### Framework versions
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- Transformers 4.
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- Pytorch 2.1
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- Datasets 2.
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- Tokenizers 0.15.
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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: Audioclasswindows
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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: 0.07964601769911504
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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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# Audioclasswindows
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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: 2.6453
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- Accuracy: 0.0796
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## Model description
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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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: 4
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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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| 2.6426 | 0.98 | 14 | 2.6541 | 0.0796 |
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| 2.6524 | 1.96 | 28 | 2.6401 | 0.0796 |
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| 2.6346 | 2.95 | 42 | 2.6441 | 0.0796 |
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| 2.6325 | 3.93 | 56 | 2.6453 | 0.0796 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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model.safetensors
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runs/Mar27_04-00-13_abd71b82d11d/events.out.tfevents.1711512015.abd71b82d11d.298.1
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