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distilhubert-finetuned-baby_cry

Audio Classification
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Files changed (6) hide show
  1. README.md +27 -22
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. runs/Jun22_12-50-50_4e4fd3ea7794/events.out.tfevents.1719060679.4e4fd3ea7794.1701.0 +3 -0
  5. runs/Jun22_12-50-50_4e4fd3ea7794/events.out.tfevents.1719061195.4e4fd3ea7794.1701.1 +3 -0
  6. training_args.bin +2 -2
README.md CHANGED
@@ -7,8 +7,9 @@ datasets:
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  - Nooon/Donate_a_cry
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  metrics:
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  - accuracy
 
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  model-index:
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- - name: distilhubert-finetuned-Donate_a_cry
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  results:
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  - task:
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  name: Audio Classification
@@ -22,22 +23,26 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9347826086956522
 
 
 
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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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  should probably proofread and complete it, then remove this comment. -->
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- # distilhubert-finetuned-Donate_a_cry
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the Donate_a_cry dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3214
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- - Accuracy: 0.9348
 
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  ## Model description
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- Baby cry classification model trained on the Donate_a_cry Dataset
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  ## Intended uses & limitations
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@@ -63,23 +68,23 @@ The following hyperparameters were used during training:
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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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- | 0.7814 | 1.0 | 52 | 0.3964 | 0.9348 |
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- | 0.7018 | 2.0 | 104 | 0.3576 | 0.9348 |
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- | 0.6262 | 3.0 | 156 | 0.3551 | 0.9348 |
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- | 0.4743 | 4.0 | 208 | 0.3489 | 0.9348 |
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- | 0.6709 | 5.0 | 260 | 0.3983 | 0.9348 |
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- | 0.5627 | 6.0 | 312 | 0.3430 | 0.9348 |
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- | 0.6891 | 7.0 | 364 | 0.3549 | 0.9348 |
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- | 0.7408 | 8.0 | 416 | 0.3505 | 0.9348 |
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- | 0.4493 | 9.0 | 468 | 0.3161 | 0.9348 |
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- | 0.2918 | 10.0 | 520 | 0.3214 | 0.9348 |
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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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  - Nooon/Donate_a_cry
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  metrics:
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  - accuracy
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+ - f1
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  model-index:
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+ - name: distilhubert-finetuned-Donate_a_cry-v2
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  results:
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  - task:
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  name: Audio Classification
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8260869565217391
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+ - name: F1
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+ type: f1
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+ value: 0.7474120082815735
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # distilhubert-finetuned-Donate_a_cry-v2
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the Donate_a_cry dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7098
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+ - Accuracy: 0.8261
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+ - F1: 0.7474
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  ## Model description
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+ More information needed
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  ## Intended uses & limitations
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.8536 | 1.0 | 52 | 0.7098 | 0.8261 | 0.7474 |
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+ | 0.6931 | 2.0 | 104 | 0.7021 | 0.8261 | 0.7474 |
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+ | 0.8844 | 3.0 | 156 | 0.6918 | 0.8261 | 0.7474 |
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+ | 0.4528 | 4.0 | 208 | 0.7020 | 0.8261 | 0.7474 |
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+ | 0.7602 | 5.0 | 260 | 0.7393 | 0.8261 | 0.7474 |
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+ | 0.6754 | 6.0 | 312 | 0.6792 | 0.8261 | 0.7474 |
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+ | 0.6515 | 7.0 | 364 | 0.6461 | 0.8261 | 0.7474 |
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+ | 0.3371 | 8.0 | 416 | 0.6750 | 0.8043 | 0.7455 |
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+ | 0.6061 | 9.0 | 468 | 0.6933 | 0.8261 | 0.7764 |
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+ | 0.2558 | 10.0 | 520 | 0.6946 | 0.8043 | 0.7703 |
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  ### Framework versions
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
config.json CHANGED
@@ -80,7 +80,7 @@
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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": "4.38.2",
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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": "4.41.2",
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  "use_weighted_layer_sum": false,
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  "vocab_size": 32
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  }
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