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distil-large-v2_ADReSSo

Audio Classification
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TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results
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End of training

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  1. README.md +35 -22
  2. model.safetensors +1 -1
  3. runs/May03_20-00-29_u22/events.out.tfevents.1746270030.u22.1291460.0 +3 -0
  4. runs/May03_20-00-29_u22/events.out.tfevents.1746271662.u22.1291460.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -24,10 +24,10 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7323943661971831
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  - name: F1
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  type: f1
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- value: 0.7532467532467533
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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
@@ -37,9 +37,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distil-whisper/distil-large-v2](https://huggingface.co/distil-whisper/distil-large-v2) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1709
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- - Accuracy: 0.7324
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- - F1: 0.7532
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  ## Model description
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@@ -73,23 +73,36 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.7006 | 1.0 | 16 | 0.6858 | 0.5952 | 0.4516 |
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- | 0.6735 | 2.0 | 32 | 0.6602 | 0.6190 | 0.4286 |
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- | 0.5912 | 3.0 | 48 | 0.6098 | 0.6667 | 0.5333 |
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- | 0.3306 | 4.0 | 64 | 1.0818 | 0.7381 | 0.6857 |
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- | 0.2717 | 5.0 | 80 | 0.9859 | 0.7619 | 0.8 |
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- | 0.1669 | 6.0 | 96 | 1.4528 | 0.7143 | 0.6471 |
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- | 0.1593 | 7.0 | 112 | 0.9437 | 0.8333 | 0.8293 |
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- | 0.2332 | 8.0 | 128 | 0.8084 | 0.7857 | 0.7805 |
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- | 0.0096 | 9.0 | 144 | 2.1995 | 0.6429 | 0.4828 |
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- | 0.1096 | 10.0 | 160 | 1.7811 | 0.6905 | 0.6486 |
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- | 0.1683 | 11.0 | 176 | 2.0866 | 0.6190 | 0.4286 |
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- | 0.1243 | 12.0 | 192 | 1.4961 | 0.7143 | 0.6667 |
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- | 0.0014 | 13.0 | 208 | 1.5052 | 0.7619 | 0.7917 |
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- | 0.089 | 14.0 | 224 | 1.3525 | 0.8095 | 0.8 |
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- | 0.0007 | 15.0 | 240 | 1.5248 | 0.7619 | 0.7727 |
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- | 0.0006 | 16.0 | 256 | 1.7027 | 0.7619 | 0.7727 |
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- | 0.0003 | 17.0 | 272 | 1.7929 | 0.7619 | 0.7727 |
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.7605633802816901
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  - name: F1
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  type: f1
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+ value: 0.7733333333333333
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  ---
32
 
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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 [distil-whisper/distil-large-v2](https://huggingface.co/distil-whisper/distil-large-v2) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.7772
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+ - Accuracy: 0.7606
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+ - F1: 0.7733
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.7 | 1.0 | 16 | 0.6865 | 0.5714 | 0.25 |
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+ | 0.6796 | 2.0 | 32 | 0.6753 | 0.5 | 0.0 |
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+ | 0.5951 | 3.0 | 48 | 0.5741 | 0.6905 | 0.6667 |
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+ | 0.3828 | 4.0 | 64 | 1.2909 | 0.5476 | 0.24 |
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+ | 0.1822 | 5.0 | 80 | 1.0336 | 0.7857 | 0.7907 |
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+ | 0.2948 | 6.0 | 96 | 0.9771 | 0.7619 | 0.7222 |
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+ | 0.064 | 7.0 | 112 | 0.9788 | 0.8333 | 0.8293 |
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+ | 0.0007 | 8.0 | 128 | 1.0079 | 0.8333 | 0.8444 |
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+ | 0.0003 | 9.0 | 144 | 1.0393 | 0.8333 | 0.8444 |
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+ | 0.0002 | 10.0 | 160 | 1.0977 | 0.8571 | 0.8696 |
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+ | 0.0001 | 11.0 | 176 | 1.1214 | 0.8571 | 0.8696 |
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+ | 0.0001 | 12.0 | 192 | 1.1597 | 0.8571 | 0.8696 |
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+ | 0.0001 | 13.0 | 208 | 1.1867 | 0.8571 | 0.8696 |
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+ | 0.0001 | 14.0 | 224 | 1.2124 | 0.8571 | 0.8696 |
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+ | 0.0001 | 15.0 | 240 | 1.2319 | 0.8571 | 0.8696 |
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+ | 0.0001 | 16.0 | 256 | 1.2440 | 0.8571 | 0.8696 |
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+ | 0.0001 | 17.0 | 272 | 1.2629 | 0.8571 | 0.8696 |
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+ | 0.0001 | 18.0 | 288 | 1.2777 | 0.8571 | 0.8696 |
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+ | 0.0001 | 19.0 | 304 | 1.2876 | 0.8571 | 0.8696 |
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+ | 0.0 | 20.0 | 320 | 1.3026 | 0.8571 | 0.8696 |
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+ | 0.0 | 21.0 | 336 | 1.3156 | 0.8571 | 0.8696 |
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+ | 0.0 | 22.0 | 352 | 1.3261 | 0.8571 | 0.8696 |
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+ | 0.0 | 23.0 | 368 | 1.3362 | 0.8571 | 0.8696 |
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+ | 0.0 | 24.0 | 384 | 1.3445 | 0.8571 | 0.8696 |
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+ | 0.0 | 25.0 | 400 | 1.3532 | 0.8571 | 0.8696 |
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+ | 0.0 | 26.0 | 416 | 1.3604 | 0.8571 | 0.8696 |
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+ | 0.0 | 27.0 | 432 | 1.3673 | 0.8571 | 0.8696 |
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+ | 0.0 | 28.0 | 448 | 1.3746 | 0.8571 | 0.8696 |
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+ | 0.0 | 29.0 | 464 | 1.3809 | 0.8571 | 0.8696 |
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+ | 0.0 | 30.0 | 480 | 1.3878 | 0.8571 | 0.8696 |
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  ### Framework versions
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