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Marcos12886
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distilhubert-finetuned-donateacry

Audio Classification
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hubert
Generated from Trainer
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Marcos12886 commited on
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End of training

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Files changed (3) hide show
  1. README.md +12 -8
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7967479674796748
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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
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.8032
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- - Accuracy: 0.7967
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  ## Model description
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@@ -61,16 +61,20 @@ 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: 4
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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 | 0.9032 | 7 | 1.0528 | 0.7317 |
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- | No log | 1.9355 | 15 | 0.9343 | 0.7724 |
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- | No log | 2.9677 | 23 | 0.8097 | 0.7967 |
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- | No log | 3.6129 | 28 | 0.8032 | 0.7967 |
 
 
 
 
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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: 0.8048780487804879
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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 [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: 0.6745
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+ - Accuracy: 0.8049
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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: 8
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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 | 0.9032 | 7 | 1.0676 | 0.7317 |
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+ | No log | 1.9355 | 15 | 0.9043 | 0.7805 |
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+ | No log | 2.9677 | 23 | 0.7870 | 0.8049 |
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+ | No log | 4.0 | 31 | 0.8390 | 0.7561 |
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+ | No log | 4.9032 | 38 | 0.7135 | 0.8130 |
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+ | No log | 5.9355 | 46 | 0.6828 | 0.8130 |
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+ | No log | 6.9677 | 54 | 0.6745 | 0.8049 |
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+ | No log | 7.2258 | 56 | 0.6745 | 0.8049 |
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  ### Framework versions
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