End of training
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README.md
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@@ -4,7 +4,7 @@ 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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- gtzan
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metrics:
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- accuracy
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model-index:
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name: Audio Classification
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type: audio-classification
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dataset:
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name:
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type: gtzan
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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.
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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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# wav2vec2-base-finetuned-gtzan
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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### Framework versions
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- Transformers 4.34.
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- Pytorch 2.0
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- Datasets 2.14.
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- Tokenizers 0.14.1
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tags:
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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metrics:
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- accuracy
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model-index:
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name: Audio Classification
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type: audio-classification
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dataset:
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name: GTZAN
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type: marsyas/gtzan
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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: 0.8
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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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# wav2vec2-base-finetuned-gtzan
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7670
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- Accuracy: 0.8
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## Model description
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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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- 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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 2.0554 | 1.0 | 100 | 2.0109 | 0.465 |
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| 1.5036 | 2.0 | 200 | 1.5547 | 0.53 |
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| 1.348 | 3.0 | 300 | 1.2558 | 0.685 |
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| 1.1877 | 4.0 | 400 | 1.1226 | 0.7 |
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| 0.8857 | 5.0 | 500 | 0.9978 | 0.76 |
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| 0.6167 | 6.0 | 600 | 0.9513 | 0.755 |
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| 0.5439 | 7.0 | 700 | 0.8185 | 0.78 |
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| 0.5015 | 8.0 | 800 | 0.7880 | 0.815 |
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| 0.2221 | 9.0 | 900 | 0.7777 | 0.8 |
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| 0.3112 | 10.0 | 1000 | 0.7670 | 0.8 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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pytorch_model.bin
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