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wav2vec2-base-finetuned-sentiment-classification-MESD

Audio Classification
Transformers
PyTorch
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: apache-2.0
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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-base-finetuned-sentiment-mesd-v11
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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-base-finetuned-sentiment-mesd-v11
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3071
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+ - Accuracy: 0.9308
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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: 0.0001
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+ - train_batch_size: 64
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+ - eval_batch_size: 40
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 256
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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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+ - num_epochs: 100
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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 | 0.86 | 3 | 1.7516 | 0.3846 |
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+ | 1.9428 | 1.86 | 6 | 1.6859 | 0.4308 |
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+ | 1.9428 | 2.86 | 9 | 1.5575 | 0.4692 |
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+ | 1.9629 | 3.86 | 12 | 1.4160 | 0.4846 |
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+ | 1.5678 | 4.86 | 15 | 1.2979 | 0.5308 |
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+ | 1.5678 | 5.86 | 18 | 1.2294 | 0.5308 |
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+ | 1.4728 | 6.86 | 21 | 1.0703 | 0.5923 |
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+ | 1.4728 | 7.86 | 24 | 0.9926 | 0.6308 |
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+ | 1.2588 | 8.86 | 27 | 0.9202 | 0.6846 |
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+ | 0.991 | 9.86 | 30 | 0.8537 | 0.6846 |
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+ | 0.991 | 10.86 | 33 | 0.8816 | 0.6769 |
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+ | 0.9059 | 11.86 | 36 | 0.7149 | 0.7769 |
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+ | 0.9059 | 12.86 | 39 | 0.7676 | 0.7462 |
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+ | 0.7901 | 13.86 | 42 | 0.6971 | 0.7538 |
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+ | 0.6278 | 14.86 | 45 | 0.6671 | 0.7923 |
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+ | 0.6278 | 15.86 | 48 | 0.5681 | 0.8231 |
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+ | 0.5678 | 16.86 | 51 | 0.5535 | 0.8154 |
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+ | 0.5678 | 17.86 | 54 | 0.5947 | 0.8077 |
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+ | 0.5157 | 18.86 | 57 | 0.6396 | 0.7692 |
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+ | 0.4189 | 19.86 | 60 | 0.5291 | 0.8077 |
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+ | 0.4189 | 20.86 | 63 | 0.4600 | 0.8538 |
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+ | 0.3885 | 21.86 | 66 | 0.5188 | 0.8308 |
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+ | 0.3885 | 22.86 | 69 | 0.5959 | 0.7923 |
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+ | 0.3255 | 23.86 | 72 | 0.5240 | 0.8462 |
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+ | 0.2711 | 24.86 | 75 | 0.5105 | 0.8385 |
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+ | 0.2711 | 25.86 | 78 | 0.5177 | 0.8231 |
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+ | 0.2748 | 26.86 | 81 | 0.3302 | 0.8923 |
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+ | 0.2748 | 27.86 | 84 | 0.4774 | 0.8538 |
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+ | 0.2379 | 28.86 | 87 | 0.4204 | 0.8769 |
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+ | 0.1982 | 29.86 | 90 | 0.6540 | 0.7692 |
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+ | 0.1982 | 30.86 | 93 | 0.5664 | 0.8308 |
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+ | 0.2171 | 31.86 | 96 | 0.5100 | 0.8462 |
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+ | 0.2171 | 32.86 | 99 | 0.3924 | 0.8769 |
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+ | 0.17 | 33.86 | 102 | 0.6002 | 0.8231 |
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+ | 0.1761 | 34.86 | 105 | 0.4364 | 0.8538 |
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+ | 0.1761 | 35.86 | 108 | 0.4166 | 0.8692 |
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+ | 0.1703 | 36.86 | 111 | 0.4374 | 0.8692 |
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+ | 0.1703 | 37.86 | 114 | 0.3872 | 0.8615 |
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+ | 0.1569 | 38.86 | 117 | 0.3941 | 0.8538 |
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+ | 0.1149 | 39.86 | 120 | 0.4004 | 0.8538 |
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+ | 0.1149 | 40.86 | 123 | 0.4360 | 0.8385 |
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+ | 0.1087 | 41.86 | 126 | 0.4387 | 0.8615 |
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+ | 0.1087 | 42.86 | 129 | 0.4352 | 0.8692 |
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+ | 0.1039 | 43.86 | 132 | 0.4018 | 0.8846 |
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+ | 0.099 | 44.86 | 135 | 0.4019 | 0.8846 |
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+ | 0.099 | 45.86 | 138 | 0.4083 | 0.8923 |
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+ | 0.1043 | 46.86 | 141 | 0.4594 | 0.8692 |
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+ | 0.1043 | 47.86 | 144 | 0.4478 | 0.8769 |
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+ | 0.0909 | 48.86 | 147 | 0.5025 | 0.8538 |
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+ | 0.1024 | 49.86 | 150 | 0.5442 | 0.8692 |
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+ | 0.1024 | 50.86 | 153 | 0.3827 | 0.8769 |
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+ | 0.1457 | 51.86 | 156 | 0.6816 | 0.8231 |
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+ | 0.1457 | 52.86 | 159 | 0.3435 | 0.8923 |
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+ | 0.1233 | 53.86 | 162 | 0.4418 | 0.8769 |
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+ | 0.101 | 54.86 | 165 | 0.4629 | 0.8846 |
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+ | 0.101 | 55.86 | 168 | 0.4616 | 0.8692 |
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+ | 0.0969 | 56.86 | 171 | 0.3608 | 0.8923 |
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+ | 0.0969 | 57.86 | 174 | 0.4867 | 0.8615 |
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+ | 0.0981 | 58.86 | 177 | 0.4493 | 0.8692 |
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+ | 0.0642 | 59.86 | 180 | 0.3841 | 0.8538 |
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+ | 0.0642 | 60.86 | 183 | 0.4509 | 0.8769 |
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+ | 0.0824 | 61.86 | 186 | 0.4477 | 0.8769 |
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+ | 0.0824 | 62.86 | 189 | 0.4649 | 0.8615 |
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+ | 0.0675 | 63.86 | 192 | 0.3492 | 0.9231 |
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+ | 0.0839 | 64.86 | 195 | 0.3763 | 0.8846 |
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+ | 0.0839 | 65.86 | 198 | 0.4475 | 0.8769 |
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+ | 0.0677 | 66.86 | 201 | 0.4104 | 0.8923 |
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+ | 0.0677 | 67.86 | 204 | 0.3071 | 0.9308 |
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+ | 0.0626 | 68.86 | 207 | 0.3598 | 0.9077 |
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+ | 0.0412 | 69.86 | 210 | 0.3771 | 0.8923 |
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+ | 0.0412 | 70.86 | 213 | 0.4043 | 0.8846 |
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+ | 0.0562 | 71.86 | 216 | 0.3696 | 0.9077 |
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+ | 0.0562 | 72.86 | 219 | 0.3295 | 0.9077 |
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+ | 0.0447 | 73.86 | 222 | 0.3616 | 0.8923 |
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+ | 0.0727 | 74.86 | 225 | 0.3495 | 0.8923 |
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+ | 0.0727 | 75.86 | 228 | 0.4330 | 0.8846 |
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+ | 0.0576 | 76.86 | 231 | 0.5179 | 0.8923 |
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+ | 0.0576 | 77.86 | 234 | 0.5544 | 0.8846 |
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+ | 0.0489 | 78.86 | 237 | 0.4630 | 0.9 |
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+ | 0.0472 | 79.86 | 240 | 0.4513 | 0.9 |
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+ | 0.0472 | 80.86 | 243 | 0.4207 | 0.9077 |
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+ | 0.0386 | 81.86 | 246 | 0.4118 | 0.8769 |
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+ | 0.0386 | 82.86 | 249 | 0.4764 | 0.8769 |
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+ | 0.0372 | 83.86 | 252 | 0.4167 | 0.8769 |
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+ | 0.0344 | 84.86 | 255 | 0.3744 | 0.9077 |
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+ | 0.0344 | 85.86 | 258 | 0.3712 | 0.9077 |
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+ | 0.0459 | 86.86 | 261 | 0.4249 | 0.8846 |
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+ | 0.0459 | 87.86 | 264 | 0.4687 | 0.8846 |
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+ | 0.0364 | 88.86 | 267 | 0.4194 | 0.8923 |
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+ | 0.0283 | 89.86 | 270 | 0.3963 | 0.8923 |
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+ | 0.0283 | 90.86 | 273 | 0.3982 | 0.8923 |
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+ | 0.0278 | 91.86 | 276 | 0.3838 | 0.9077 |
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+ | 0.0278 | 92.86 | 279 | 0.3731 | 0.9 |
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+ | 0.0352 | 93.86 | 282 | 0.3736 | 0.9 |
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+ | 0.0297 | 94.86 | 285 | 0.3702 | 0.9 |
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+ | 0.0297 | 95.86 | 288 | 0.3521 | 0.9154 |
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+ | 0.0245 | 96.86 | 291 | 0.3522 | 0.9154 |
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+ | 0.0245 | 97.86 | 294 | 0.3600 | 0.9077 |
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+ | 0.0241 | 98.86 | 297 | 0.3636 | 0.9077 |
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+ | 0.0284 | 99.86 | 300 | 0.3639 | 0.9077 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.17.0
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 2.0.0
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+ - Tokenizers 0.11.6