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hubert-classifier-aug

Audio Classification
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Safetensors
hubert
Generated from Trainer
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  1. README.md +18 -18
  2. runs/Jul18_15-38-49_LAPTOP-1GID9RGH/events.out.tfevents.1721291930.LAPTOP-1GID9RGH.11916.1 +2 -2
  3. runs/Jul18_15-38-49_LAPTOP-1GID9RGH/events.out.tfevents.1721292389.LAPTOP-1GID9RGH.11916.2 +3 -0
README.md CHANGED
@@ -20,7 +20,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 4.4213
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  - Accuracy: 0.0148
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  - Precision: 0.0002
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  - Recall: 0.0148
@@ -59,23 +59,23 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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- | No log | 0.15 | 50 | 4.4256 | 0.0121 | 0.0001 | 0.0121 | 0.0003 | 0.1243 |
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- | No log | 0.31 | 100 | 4.4222 | 0.0135 | 0.0002 | 0.0135 | 0.0004 | 0.1333 |
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- | No log | 0.46 | 150 | 4.4227 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1352 |
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- | No log | 0.62 | 200 | 4.4228 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1371 |
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- | No log | 0.77 | 250 | 4.4222 | 0.0135 | 0.0002 | 0.0135 | 0.0004 | 0.1264 |
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- | No log | 0.92 | 300 | 4.4226 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1371 |
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- | No log | 1.08 | 350 | 4.4219 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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- | No log | 1.23 | 400 | 4.4221 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1261 |
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- | No log | 1.39 | 450 | 4.4221 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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- | 4.4251 | 1.54 | 500 | 4.4213 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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- | 4.4251 | 1.69 | 550 | 4.4215 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1352 |
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- | 4.4251 | 1.85 | 600 | 4.4210 | 0.0135 | 0.0002 | 0.0135 | 0.0004 | 0.1333 |
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- | 4.4251 | 2.0 | 650 | 4.4214 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1371 |
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- | 4.4251 | 2.16 | 700 | 4.4229 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1371 |
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- | 4.4251 | 2.31 | 750 | 4.4208 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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- | 4.4251 | 2.47 | 800 | 4.4214 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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- | 4.4251 | 2.62 | 850 | 4.4207 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1371 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 4.4216
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  - Accuracy: 0.0148
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  - Precision: 0.0002
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  - Recall: 0.0148
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | No log | 0.15 | 50 | 4.4273 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1371 |
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+ | No log | 0.31 | 100 | 4.4237 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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+ | No log | 0.46 | 150 | 4.4239 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1352 |
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+ | No log | 0.62 | 200 | 4.4237 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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+ | No log | 0.77 | 250 | 4.4218 | 0.0135 | 0.0002 | 0.0135 | 0.0004 | 0.1264 |
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+ | No log | 0.92 | 300 | 4.4224 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1371 |
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+ | No log | 1.08 | 350 | 4.4214 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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+ | No log | 1.23 | 400 | 4.4213 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1261 |
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+ | No log | 1.39 | 450 | 4.4209 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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+ | 4.4252 | 1.54 | 500 | 4.4216 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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+ | 4.4252 | 1.69 | 550 | 4.4213 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1302 |
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+ | 4.4252 | 1.85 | 600 | 4.4208 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1371 |
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+ | 4.4252 | 2.0 | 650 | 4.4211 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1371 |
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+ | 4.4252 | 2.16 | 700 | 4.4231 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1371 |
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+ | 4.4252 | 2.31 | 750 | 4.4209 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1283 |
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+ | 4.4252 | 2.47 | 800 | 4.4209 | 0.0135 | 0.0002 | 0.0135 | 0.0004 | 0.1233 |
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+ | 4.4252 | 2.62 | 850 | 4.4215 | 0.0148 | 0.0002 | 0.0148 | 0.0004 | 0.1261 |
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  ### Framework versions
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