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wav2vec2-base

Audio Classification
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Safetensors
wav2vec2
Generated from Trainer
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End of training

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  1. README.md +51 -9
  2. model.safetensors +1 -1
  3. runs/Feb08_11-19-29_40e28f1b8553/events.out.tfevents.1707391183.40e28f1b8553.157.0 +2 -2
  4. runs/Feb08_11-19-29_40e28f1b8553/events.out.tfevents.1707392111.40e28f1b8553.157.1 +3 -0
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.6714
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- - Accuracy: 0.1916
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  ## Model description
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@@ -37,7 +37,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -46,17 +46,59 @@ The following hyperparameters were used during training:
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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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- - 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 | 9 | 2.6714 | 0.1916 |
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- | 2.7326 | 2.0 | 18 | 2.5486 | 0.1916 |
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- | 2.5634 | 3.0 | 27 | 2.4935 | 0.1916 |
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- | 2.4739 | 4.0 | 36 | 2.4752 | 0.1916 |
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- | 2.4478 | 5.0 | 45 | 2.4672 | 0.1916 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5735
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+ - Accuracy: 0.8913
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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  - train_batch_size: 32
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  - eval_batch_size: 32
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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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+ - num_epochs: 50
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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 | 0.92 | 3 | 2.7459 | 0.1304 |
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+ | No log | 1.85 | 6 | 2.6837 | 0.1087 |
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+ | No log | 2.77 | 9 | 2.6583 | 0.1087 |
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+ | 2.6599 | 4.0 | 13 | 2.6553 | 0.1087 |
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+ | 2.6599 | 4.92 | 16 | 2.5628 | 0.1522 |
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+ | 2.6599 | 5.85 | 19 | 2.4286 | 0.1739 |
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+ | 2.3457 | 6.77 | 22 | 2.4705 | 0.1522 |
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+ | 2.3457 | 8.0 | 26 | 2.2801 | 0.1522 |
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+ | 2.3457 | 8.92 | 29 | 2.2110 | 0.2391 |
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+ | 2.1136 | 9.85 | 32 | 2.1101 | 0.2391 |
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+ | 2.1136 | 10.77 | 35 | 2.0434 | 0.3478 |
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+ | 2.1136 | 12.0 | 39 | 2.2015 | 0.2609 |
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+ | 1.8271 | 12.92 | 42 | 1.8463 | 0.2826 |
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+ | 1.8271 | 13.85 | 45 | 1.8144 | 0.2391 |
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+ | 1.8271 | 14.77 | 48 | 1.6712 | 0.2391 |
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+ | 1.6517 | 16.0 | 52 | 1.6885 | 0.4348 |
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+ | 1.6517 | 16.92 | 55 | 1.7268 | 0.4565 |
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+ | 1.6517 | 17.85 | 58 | 1.5564 | 0.5435 |
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+ | 1.5123 | 18.77 | 61 | 1.4261 | 0.5435 |
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+ | 1.5123 | 20.0 | 65 | 1.2945 | 0.6739 |
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+ | 1.5123 | 20.92 | 68 | 1.2329 | 0.6957 |
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+ | 1.2441 | 21.85 | 71 | 1.1841 | 0.6957 |
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+ | 1.2441 | 22.77 | 74 | 1.1297 | 0.7174 |
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+ | 1.2441 | 24.0 | 78 | 1.0477 | 0.7826 |
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+ | 1.0647 | 24.92 | 81 | 1.0039 | 0.7174 |
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+ | 1.0647 | 25.85 | 84 | 0.9795 | 0.7174 |
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+ | 1.0647 | 26.77 | 87 | 0.9619 | 0.7609 |
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+ | 0.9374 | 28.0 | 91 | 0.8940 | 0.8043 |
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+ | 0.9374 | 28.92 | 94 | 0.8675 | 0.8043 |
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+ | 0.9374 | 29.85 | 97 | 0.8516 | 0.8043 |
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+ | 0.7902 | 30.77 | 100 | 0.8203 | 0.8261 |
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+ | 0.7902 | 32.0 | 104 | 0.7963 | 0.7609 |
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+ | 0.7902 | 32.92 | 107 | 0.7329 | 0.8478 |
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+ | 0.6959 | 33.85 | 110 | 0.7382 | 0.8043 |
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+ | 0.6959 | 34.77 | 113 | 0.7205 | 0.8261 |
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+ | 0.6959 | 36.0 | 117 | 0.6996 | 0.8043 |
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+ | 0.6694 | 36.92 | 120 | 0.6949 | 0.8696 |
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+ | 0.6694 | 37.85 | 123 | 0.7009 | 0.7826 |
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+ | 0.6694 | 38.77 | 126 | 0.6502 | 0.8261 |
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+ | 0.6226 | 40.0 | 130 | 0.5835 | 0.8478 |
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+ | 0.6226 | 40.92 | 133 | 0.5735 | 0.8913 |
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+ | 0.6226 | 41.85 | 136 | 0.5651 | 0.8913 |
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+ | 0.6226 | 42.77 | 139 | 0.5624 | 0.8913 |
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+ | 0.5746 | 44.0 | 143 | 0.5565 | 0.8913 |
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+ | 0.5746 | 44.92 | 146 | 0.5476 | 0.8913 |
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+ | 0.5746 | 45.85 | 149 | 0.5439 | 0.8913 |
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+ | 0.5238 | 46.15 | 150 | 0.5435 | 0.8913 |
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  ### Framework versions
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