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End of training

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  1. README.md +20 -22
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -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:
@@ -14,15 +14,15 @@ 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: 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: 0.85
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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
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.9600
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- - Accuracy: 0.85
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  ## Model description
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@@ -56,8 +56,6 @@ The following hyperparameters were used during training:
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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
@@ -67,21 +65,21 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.2696 | 0.99 | 28 | 2.1350 | 0.45 |
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- | 1.9724 | 1.98 | 56 | 1.7939 | 0.63 |
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- | 1.7172 | 2.97 | 84 | 1.6356 | 0.58 |
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- | 1.5428 | 4.0 | 113 | 1.4019 | 0.71 |
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- | 1.3184 | 4.99 | 141 | 1.3236 | 0.73 |
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- | 1.2897 | 5.98 | 169 | 1.1980 | 0.79 |
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- | 1.1657 | 6.97 | 197 | 1.0928 | 0.84 |
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- | 1.0407 | 8.0 | 226 | 1.0616 | 0.83 |
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- | 0.9717 | 8.99 | 254 | 0.9931 | 0.87 |
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- | 0.9158 | 9.91 | 280 | 0.9600 | 0.85 |
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  ### Framework versions
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- - Transformers 4.34.0
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- - Pytorch 2.0.1+cu118
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- - Datasets 2.14.5
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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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