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End of training

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  1. README.md +11 -13
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.78
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [yuval6967/wav2vec2-base-finetuned-gtzan](https://huggingface.co/yuval6967/wav2vec2-base-finetuned-gtzan) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3065
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- - Accuracy: 0.78
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  ## Model description
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@@ -53,27 +53,25 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 4
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- - eval_batch_size: 4
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  - seed: 42
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  - gradient_accumulation_steps: 2
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- - total_train_batch_size: 8
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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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- - mixed_precision_training: Native AMP
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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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- | 0.6708 | 0.9956 | 112 | 1.2056 | 0.75 |
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- | 0.6752 | 2.0 | 225 | 1.1245 | 0.78 |
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- | 0.1894 | 2.9956 | 337 | 1.0640 | 0.81 |
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- | 0.2192 | 4.0 | 450 | 1.3034 | 0.76 |
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- | 0.2675 | 4.9956 | 562 | 1.0633 | 0.81 |
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- | 0.1237 | 6.0 | 675 | 1.3065 | 0.78 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.82
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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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  This model is a fine-tuned version of [yuval6967/wav2vec2-base-finetuned-gtzan](https://huggingface.co/yuval6967/wav2vec2-base-finetuned-gtzan) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8942
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+ - Accuracy: 0.82
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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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: 2
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+ - total_train_batch_size: 16
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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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+ | 0.4822 | 0.9912 | 56 | 1.2225 | 0.78 |
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+ | 0.3026 | 2.0 | 113 | 0.7599 | 0.85 |
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+ | 0.2191 | 2.9912 | 169 | 0.8816 | 0.8 |
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+ | 0.0791 | 4.0 | 226 | 1.1267 | 0.78 |
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+ | 0.092 | 4.9912 | 282 | 0.8942 | 0.82 |
 
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  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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