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wav2vec2-5Class-train-test-finetune-V7

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
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  1. README.md +293 -0
  2. model.safetensors +1 -1
  3. runs/Jun22_12-01-17_ml6.hpc.uio.no/events.out.tfevents.1719050520.ml6.hpc.uio.no.238353.0 +2 -2
README.md ADDED
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+ ---
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+ base_model: anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: wav2vec2-5Class-train-test-finetune-V7
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+ results: []
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+ ---
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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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+
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+ # wav2vec2-5Class-train-test-finetune-V7
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+
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+ This model is a fine-tuned version of [anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test](https://huggingface.co/anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9666
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+ - Accuracy: 0.6503
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 128
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+ - eval_batch_size: 128
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+ - seed: 0
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 512
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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: 250.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | No log | 0.92 | 3 | 1.6026 | 0.1608 |
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+ | No log | 1.85 | 6 | 1.6024 | 0.1608 |
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+ | No log | 2.77 | 9 | 1.6021 | 0.1608 |
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+ | No log | 4.0 | 13 | 1.6014 | 0.1608 |
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+ | No log | 4.92 | 16 | 1.6008 | 0.1608 |
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+ | No log | 5.85 | 19 | 1.6001 | 0.1608 |
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+ | No log | 6.77 | 22 | 1.5992 | 0.1608 |
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+ | No log | 8.0 | 26 | 1.5978 | 0.1748 |
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+ | No log | 8.92 | 29 | 1.5965 | 0.1888 |
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+ | No log | 9.85 | 32 | 1.5952 | 0.2098 |
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+ | No log | 10.77 | 35 | 1.5938 | 0.2273 |
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+ | No log | 12.0 | 39 | 1.5916 | 0.2343 |
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+ | No log | 12.92 | 42 | 1.5899 | 0.2692 |
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+ | No log | 13.85 | 45 | 1.5880 | 0.2727 |
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+ | No log | 14.77 | 48 | 1.5860 | 0.3077 |
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+ | No log | 16.0 | 52 | 1.5833 | 0.3566 |
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+ | No log | 16.92 | 55 | 1.5811 | 0.3881 |
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+ | No log | 17.85 | 58 | 1.5788 | 0.3811 |
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+ | No log | 18.77 | 61 | 1.5764 | 0.3671 |
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+ | No log | 20.0 | 65 | 1.5731 | 0.3497 |
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+ | No log | 20.92 | 68 | 1.5702 | 0.3287 |
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+ | No log | 21.85 | 71 | 1.5672 | 0.3252 |
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+ | No log | 22.77 | 74 | 1.5641 | 0.3147 |
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+ | No log | 24.0 | 78 | 1.5597 | 0.3112 |
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+ | No log | 24.92 | 81 | 1.5564 | 0.3077 |
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+ | No log | 25.85 | 84 | 1.5532 | 0.3042 |
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+ | No log | 26.77 | 87 | 1.5499 | 0.2937 |
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+ | No log | 28.0 | 91 | 1.5454 | 0.2902 |
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+ | No log | 28.92 | 94 | 1.5419 | 0.2867 |
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+ | No log | 29.85 | 97 | 1.5383 | 0.2832 |
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+ | 1.5563 | 30.77 | 100 | 1.5349 | 0.2762 |
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+ | 1.5563 | 32.0 | 104 | 1.5304 | 0.2797 |
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+ | 1.5563 | 32.92 | 107 | 1.5273 | 0.2762 |
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+ | 1.5563 | 33.85 | 110 | 1.5247 | 0.2657 |
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+ | 1.5563 | 34.77 | 113 | 1.5223 | 0.2517 |
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+ | 1.5563 | 36.0 | 117 | 1.5194 | 0.2483 |
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+ | 1.5563 | 36.92 | 120 | 1.5178 | 0.2413 |
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+ | 1.5563 | 37.85 | 123 | 1.5168 | 0.2378 |
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+ | 1.5563 | 38.77 | 126 | 1.5162 | 0.2448 |
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+ | 1.5563 | 40.0 | 130 | 1.5162 | 0.2448 |
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+ | 1.5563 | 40.92 | 133 | 1.5167 | 0.2483 |
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+ | 1.5563 | 41.85 | 136 | 1.5181 | 0.2483 |
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+ | 1.5563 | 42.77 | 139 | 1.5203 | 0.2587 |
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+ | 1.5563 | 44.0 | 143 | 1.5227 | 0.2692 |
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+ | 1.5563 | 44.92 | 146 | 1.5243 | 0.2832 |
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+ | 1.5563 | 45.85 | 149 | 1.5239 | 0.2797 |
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+ | 1.5563 | 46.77 | 152 | 1.5224 | 0.3007 |
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+ | 1.5563 | 48.0 | 156 | 1.5170 | 0.3077 |
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+ | 1.5563 | 48.92 | 159 | 1.5103 | 0.3287 |
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+ | 1.5563 | 49.85 | 162 | 1.5032 | 0.3497 |
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+ | 1.5563 | 50.77 | 165 | 1.4959 | 0.3601 |
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+ | 1.5563 | 52.0 | 169 | 1.4857 | 0.3636 |
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+ | 1.5563 | 52.92 | 172 | 1.4788 | 0.3671 |
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+ | 1.5563 | 53.85 | 175 | 1.4713 | 0.3741 |
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+ | 1.5563 | 54.77 | 178 | 1.4642 | 0.3811 |
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+ | 1.5563 | 56.0 | 182 | 1.4553 | 0.3881 |
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+ | 1.5563 | 56.92 | 185 | 1.4481 | 0.3986 |
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+ | 1.5563 | 57.85 | 188 | 1.4421 | 0.4021 |
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+ | 1.5563 | 58.77 | 191 | 1.4357 | 0.4126 |
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+ | 1.5563 | 60.0 | 195 | 1.4284 | 0.4196 |
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+ | 1.5563 | 60.92 | 198 | 1.4218 | 0.4196 |
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+ | 1.3138 | 61.85 | 201 | 1.4167 | 0.4301 |
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+ | 1.3138 | 62.77 | 204 | 1.4091 | 0.4301 |
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+ | 1.3138 | 64.0 | 208 | 1.3995 | 0.4371 |
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+ | 1.3138 | 64.92 | 211 | 1.3911 | 0.4406 |
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+ | 1.3138 | 65.85 | 214 | 1.3825 | 0.4336 |
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+ | 1.3138 | 66.77 | 217 | 1.3735 | 0.4441 |
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+ | 1.3138 | 68.0 | 221 | 1.3632 | 0.4476 |
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+ | 1.3138 | 68.92 | 224 | 1.3556 | 0.4510 |
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+ | 1.3138 | 69.85 | 227 | 1.3492 | 0.4510 |
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+ | 1.3138 | 70.77 | 230 | 1.3441 | 0.4510 |
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+ | 1.3138 | 72.0 | 234 | 1.3352 | 0.4580 |
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+ | 1.3138 | 72.92 | 237 | 1.3269 | 0.4615 |
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+ | 1.3138 | 73.85 | 240 | 1.3186 | 0.4755 |
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+ | 1.3138 | 74.77 | 243 | 1.3105 | 0.4755 |
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+ | 1.3138 | 76.0 | 247 | 1.2992 | 0.4790 |
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+ | 1.3138 | 76.92 | 250 | 1.2896 | 0.4825 |
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+ | 1.3138 | 77.85 | 253 | 1.2797 | 0.4825 |
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+ | 1.3138 | 78.77 | 256 | 1.2707 | 0.4860 |
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+ | 1.3138 | 80.0 | 260 | 1.2587 | 0.4930 |
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+ | 1.3138 | 80.92 | 263 | 1.2494 | 0.4930 |
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+ | 1.3138 | 81.85 | 266 | 1.2407 | 0.4930 |
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+ | 1.3138 | 82.77 | 269 | 1.2314 | 0.5105 |
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+ | 1.3138 | 84.0 | 273 | 1.2205 | 0.5140 |
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+ | 1.3138 | 84.92 | 276 | 1.2124 | 0.5210 |
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+ | 1.3138 | 85.85 | 279 | 1.2043 | 0.5315 |
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+ | 1.3138 | 86.77 | 282 | 1.1973 | 0.5350 |
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+ | 1.3138 | 88.0 | 286 | 1.1870 | 0.5524 |
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+ | 1.3138 | 88.92 | 289 | 1.1788 | 0.5629 |
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+ | 1.3138 | 89.85 | 292 | 1.1700 | 0.5629 |
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+ | 1.3138 | 90.77 | 295 | 1.1613 | 0.5699 |
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+ | 1.3138 | 92.0 | 299 | 1.1498 | 0.5839 |
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+ | 1.047 | 92.92 | 302 | 1.1411 | 0.5874 |
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+ | 1.047 | 93.85 | 305 | 1.1330 | 0.5944 |
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+ | 1.047 | 94.77 | 308 | 1.1261 | 0.5944 |
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+ | 1.047 | 96.0 | 312 | 1.1161 | 0.6014 |
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+ | 1.047 | 96.92 | 315 | 1.1084 | 0.6014 |
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+ | 1.047 | 97.85 | 318 | 1.1003 | 0.6049 |
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+ | 1.047 | 98.77 | 321 | 1.0926 | 0.6049 |
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+ | 1.047 | 100.0 | 325 | 1.0821 | 0.6084 |
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+ | 1.047 | 100.92 | 328 | 1.0754 | 0.6084 |
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+ | 1.047 | 101.85 | 331 | 1.0690 | 0.6084 |
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+ | 1.047 | 102.77 | 334 | 1.0637 | 0.6154 |
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+ | 1.047 | 104.0 | 338 | 1.0549 | 0.6189 |
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+ | 1.047 | 104.92 | 341 | 1.0478 | 0.6224 |
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+ | 1.047 | 105.85 | 344 | 1.0420 | 0.6259 |
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+ | 1.047 | 106.77 | 347 | 1.0370 | 0.6294 |
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+ | 1.047 | 108.0 | 351 | 1.0308 | 0.6294 |
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+ | 1.047 | 108.92 | 354 | 1.0263 | 0.6259 |
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+ | 1.047 | 109.85 | 357 | 1.0231 | 0.6259 |
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+ | 1.047 | 110.77 | 360 | 1.0204 | 0.6329 |
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+ | 1.047 | 112.0 | 364 | 1.0167 | 0.6294 |
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+ | 1.047 | 112.92 | 367 | 1.0145 | 0.6294 |
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+ | 1.047 | 113.85 | 370 | 1.0119 | 0.6329 |
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+ | 1.047 | 114.77 | 373 | 1.0077 | 0.6294 |
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+ | 1.047 | 116.0 | 377 | 1.0012 | 0.6364 |
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+ | 1.047 | 116.92 | 380 | 0.9975 | 0.6364 |
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+ | 1.047 | 117.85 | 383 | 0.9938 | 0.6364 |
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+ | 1.047 | 118.77 | 386 | 0.9913 | 0.6399 |
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+ | 1.047 | 120.0 | 390 | 0.9886 | 0.6469 |
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+ | 1.047 | 120.92 | 393 | 0.9870 | 0.6469 |
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+ | 1.047 | 121.85 | 396 | 0.9861 | 0.6399 |
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+ | 1.047 | 122.77 | 399 | 0.9857 | 0.6434 |
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+ | 0.8183 | 124.0 | 403 | 0.9855 | 0.6399 |
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+ | 0.8183 | 124.92 | 406 | 0.9864 | 0.6399 |
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+ | 0.8183 | 125.85 | 409 | 0.9857 | 0.6399 |
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+ | 0.8183 | 126.77 | 412 | 0.9818 | 0.6399 |
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+ | 0.8183 | 128.0 | 416 | 0.9765 | 0.6399 |
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+ | 0.8183 | 128.92 | 419 | 0.9740 | 0.6399 |
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+ | 0.8183 | 129.85 | 422 | 0.9737 | 0.6434 |
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+ | 0.8183 | 130.77 | 425 | 0.9754 | 0.6469 |
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+ | 0.8183 | 132.0 | 429 | 0.9753 | 0.6469 |
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+ | 0.8183 | 132.92 | 432 | 0.9740 | 0.6469 |
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+ | 0.8183 | 133.85 | 435 | 0.9710 | 0.6469 |
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+ | 0.8183 | 134.77 | 438 | 0.9686 | 0.6469 |
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+ | 0.8183 | 136.0 | 442 | 0.9671 | 0.6469 |
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+ | 0.8183 | 136.92 | 445 | 0.9669 | 0.6434 |
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+ | 0.8183 | 137.85 | 448 | 0.9659 | 0.6399 |
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+ | 0.8183 | 138.77 | 451 | 0.9662 | 0.6434 |
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+ | 0.8183 | 140.0 | 455 | 0.9674 | 0.6434 |
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+ | 0.8183 | 140.92 | 458 | 0.9694 | 0.6399 |
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+ | 0.8183 | 141.85 | 461 | 0.9716 | 0.6469 |
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+ | 0.8183 | 142.77 | 464 | 0.9739 | 0.6434 |
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+ | 0.8183 | 144.0 | 468 | 0.9712 | 0.6469 |
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+ | 0.8183 | 144.92 | 471 | 0.9670 | 0.6434 |
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+ | 0.8183 | 145.85 | 474 | 0.9637 | 0.6434 |
201
+ | 0.8183 | 146.77 | 477 | 0.9625 | 0.6469 |
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+ | 0.8183 | 149.85 | 487 | 0.9663 | 0.6469 |
205
+ | 0.8183 | 150.77 | 490 | 0.9649 | 0.6503 |
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+ | 0.8183 | 152.0 | 494 | 0.9655 | 0.6503 |
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+ | 0.8183 | 152.92 | 497 | 0.9648 | 0.6503 |
208
+ | 0.7321 | 153.85 | 500 | 0.9638 | 0.6503 |
209
+ | 0.7321 | 154.77 | 503 | 0.9631 | 0.6503 |
210
+ | 0.7321 | 156.0 | 507 | 0.9647 | 0.6503 |
211
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212
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+ | 0.7321 | 158.77 | 516 | 0.9679 | 0.6503 |
214
+ | 0.7321 | 160.0 | 520 | 0.9675 | 0.6503 |
215
+ | 0.7321 | 160.92 | 523 | 0.9664 | 0.6503 |
216
+ | 0.7321 | 161.85 | 526 | 0.9655 | 0.6503 |
217
+ | 0.7321 | 162.77 | 529 | 0.9642 | 0.6503 |
218
+ | 0.7321 | 164.0 | 533 | 0.9635 | 0.6503 |
219
+ | 0.7321 | 164.92 | 536 | 0.9633 | 0.6503 |
220
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221
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+ | 0.7321 | 168.0 | 546 | 0.9651 | 0.6503 |
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+ | 0.7321 | 168.92 | 549 | 0.9657 | 0.6503 |
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+ | 0.7321 | 169.85 | 552 | 0.9663 | 0.6538 |
225
+ | 0.7321 | 170.77 | 555 | 0.9653 | 0.6503 |
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227
+ | 0.7321 | 172.92 | 562 | 0.9616 | 0.6503 |
228
+ | 0.7321 | 173.85 | 565 | 0.9601 | 0.6503 |
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+ | 0.7321 | 174.77 | 568 | 0.9610 | 0.6538 |
230
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231
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232
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233
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234
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235
+ | 0.7321 | 180.92 | 588 | 0.9680 | 0.6503 |
236
+ | 0.7321 | 181.85 | 591 | 0.9687 | 0.6503 |
237
+ | 0.7321 | 182.77 | 594 | 0.9692 | 0.6503 |
238
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239
+ | 0.6941 | 184.92 | 601 | 0.9677 | 0.6503 |
240
+ | 0.6941 | 185.85 | 604 | 0.9674 | 0.6503 |
241
+ | 0.6941 | 186.77 | 607 | 0.9671 | 0.6503 |
242
+ | 0.6941 | 188.0 | 611 | 0.9670 | 0.6503 |
243
+ | 0.6941 | 188.92 | 614 | 0.9662 | 0.6503 |
244
+ | 0.6941 | 189.85 | 617 | 0.9653 | 0.6503 |
245
+ | 0.6941 | 190.77 | 620 | 0.9645 | 0.6503 |
246
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247
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248
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249
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250
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251
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252
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253
+ | 0.6941 | 198.77 | 646 | 0.9674 | 0.6434 |
254
+ | 0.6941 | 200.0 | 650 | 0.9669 | 0.6469 |
255
+ | 0.6941 | 200.92 | 653 | 0.9672 | 0.6469 |
256
+ | 0.6941 | 201.85 | 656 | 0.9671 | 0.6469 |
257
+ | 0.6941 | 202.77 | 659 | 0.9673 | 0.6503 |
258
+ | 0.6941 | 204.0 | 663 | 0.9666 | 0.6503 |
259
+ | 0.6941 | 204.92 | 666 | 0.9660 | 0.6503 |
260
+ | 0.6941 | 205.85 | 669 | 0.9656 | 0.6503 |
261
+ | 0.6941 | 206.77 | 672 | 0.9651 | 0.6503 |
262
+ | 0.6941 | 208.0 | 676 | 0.9661 | 0.6503 |
263
+ | 0.6941 | 208.92 | 679 | 0.9667 | 0.6503 |
264
+ | 0.6941 | 209.85 | 682 | 0.9668 | 0.6503 |
265
+ | 0.6941 | 210.77 | 685 | 0.9669 | 0.6503 |
266
+ | 0.6941 | 212.0 | 689 | 0.9665 | 0.6503 |
267
+ | 0.6941 | 212.92 | 692 | 0.9665 | 0.6503 |
268
+ | 0.6941 | 213.85 | 695 | 0.9664 | 0.6503 |
269
+ | 0.6941 | 214.77 | 698 | 0.9663 | 0.6503 |
270
+ | 0.6696 | 216.0 | 702 | 0.9666 | 0.6503 |
271
+ | 0.6696 | 216.92 | 705 | 0.9667 | 0.6503 |
272
+ | 0.6696 | 217.85 | 708 | 0.9665 | 0.6503 |
273
+ | 0.6696 | 218.77 | 711 | 0.9663 | 0.6503 |
274
+ | 0.6696 | 220.0 | 715 | 0.9661 | 0.6503 |
275
+ | 0.6696 | 220.92 | 718 | 0.9661 | 0.6503 |
276
+ | 0.6696 | 221.85 | 721 | 0.9662 | 0.6503 |
277
+ | 0.6696 | 222.77 | 724 | 0.9664 | 0.6503 |
278
+ | 0.6696 | 224.0 | 728 | 0.9664 | 0.6503 |
279
+ | 0.6696 | 224.92 | 731 | 0.9664 | 0.6503 |
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+ | 0.6696 | 225.85 | 734 | 0.9666 | 0.6503 |
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+ | 0.6696 | 226.77 | 737 | 0.9666 | 0.6503 |
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+ | 0.6696 | 228.0 | 741 | 0.9665 | 0.6503 |
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+ | 0.6696 | 228.92 | 744 | 0.9666 | 0.6503 |
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+ | 0.6696 | 229.85 | 747 | 0.9666 | 0.6503 |
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+ | 0.6696 | 230.77 | 750 | 0.9666 | 0.6503 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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