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End of training

Browse files
README.md CHANGED
@@ -5,9 +5,24 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - audiofolder
 
 
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  model-index:
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  - name: distilhubert-finetuned-cry-detector
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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
@@ -16,6 +31,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilhubert-finetuned-cry-detector
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
 
 
 
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  ## Model description
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@@ -42,18 +60,22 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 64
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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- - num_epochs: 1
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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 | 1.0 | 11 | 0.3065 | 0.9605 |
 
 
 
 
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  ### Framework versions
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- - Transformers 4.42.3
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  - Pytorch 2.3.1+cu118
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  - Datasets 2.20.0
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  - Tokenizers 0.19.1
 
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  - generated_from_trainer
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  datasets:
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  - audiofolder
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+ metrics:
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+ - accuracy
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  model-index:
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  - name: distilhubert-finetuned-cry-detector
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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: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.96045197740113
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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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  # distilhubert-finetuned-cry-detector
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0929
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+ - Accuracy: 0.9605
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  ## Model description
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  - total_train_batch_size: 64
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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+ - num_epochs: 5
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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 | 1.0 | 11 | 0.1843 | 0.9322 |
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+ | No log | 2.0 | 22 | 0.1730 | 0.9379 |
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+ | No log | 3.0 | 33 | 0.1143 | 0.9492 |
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+ | No log | 4.0 | 44 | 0.0885 | 0.9661 |
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+ | No log | 5.0 | 55 | 0.0929 | 0.9605 |
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  ### Framework versions
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+ - Transformers 4.43.4
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  - Pytorch 2.3.1+cu118
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  - Datasets 2.20.0
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  - Tokenizers 0.19.1
config.json CHANGED
@@ -74,7 +74,7 @@
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  "num_hidden_layers": 2,
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  "pad_token_id": 0,
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  "torch_dtype": "float32",
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- "transformers_version": "4.42.3",
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  "use_weighted_layer_sum": false,
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  "vocab_size": 32
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  }
 
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  "num_hidden_layers": 2,
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  "pad_token_id": 0,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.43.4",
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  "use_weighted_layer_sum": false,
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  "vocab_size": 32
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  }
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