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urdu-emotions-wav2vec2-large-xlsr

Audio Classification
Transformers
PyTorch
TensorBoard
Urdu
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
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  2. pytorch_model.bin +1 -1
  3. runs/Mar10_16-01-12_6c602116be73/events.out.tfevents.1710086484.6c602116be73.17.2 +2 -2
README.md ADDED
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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: urdu-emotions
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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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+ # urdu-emotions
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0077
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+ - Accuracy: 1.0
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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: 5e-05
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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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+ - num_epochs: 50
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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 | 1.0 | 8 | 1.0905 | 0.4833 |
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+ | 1.0739 | 2.0 | 16 | 1.0736 | 0.5 |
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+ | 1.0341 | 3.0 | 24 | 0.9888 | 0.75 |
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+ | 0.9797 | 4.0 | 32 | 0.9144 | 0.7667 |
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+ | 0.8716 | 5.0 | 40 | 0.8531 | 0.75 |
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+ | 0.8716 | 6.0 | 48 | 0.7572 | 0.75 |
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+ | 0.7905 | 7.0 | 56 | 0.6556 | 0.7333 |
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+ | 0.6837 | 8.0 | 64 | 0.5976 | 0.7167 |
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+ | 0.6611 | 9.0 | 72 | 0.5298 | 0.7667 |
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+ | 0.5744 | 10.0 | 80 | 0.5014 | 0.8 |
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+ | 0.5744 | 11.0 | 88 | 0.4616 | 0.8667 |
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+ | 0.5402 | 12.0 | 96 | 0.3964 | 0.9667 |
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+ | 0.4185 | 13.0 | 104 | 0.3536 | 0.8833 |
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+ | 0.4138 | 14.0 | 112 | 0.2818 | 0.9167 |
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+ | 0.3409 | 15.0 | 120 | 0.2554 | 0.9333 |
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+ | 0.3409 | 16.0 | 128 | 0.1434 | 0.9833 |
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+ | 0.2923 | 17.0 | 136 | 0.1658 | 0.95 |
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+ | 0.2412 | 18.0 | 144 | 0.0775 | 1.0 |
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+ | 0.2038 | 19.0 | 152 | 0.0766 | 1.0 |
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+ | 0.1618 | 20.0 | 160 | 0.0680 | 1.0 |
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+ | 0.1618 | 21.0 | 168 | 0.0517 | 1.0 |
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+ | 0.2041 | 22.0 | 176 | 0.0344 | 1.0 |
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+ | 0.1238 | 23.0 | 184 | 0.0313 | 1.0 |
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+ | 0.1179 | 24.0 | 192 | 0.0269 | 1.0 |
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+ | 0.1738 | 25.0 | 200 | 0.0248 | 1.0 |
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+ | 0.1738 | 26.0 | 208 | 0.0213 | 1.0 |
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+ | 0.1265 | 27.0 | 216 | 0.0363 | 0.9833 |
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+ | 0.1503 | 28.0 | 224 | 0.1058 | 0.9667 |
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+ | 0.1201 | 29.0 | 232 | 0.0270 | 1.0 |
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+ | 0.0484 | 30.0 | 240 | 0.1284 | 0.9667 |
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+ | 0.0484 | 31.0 | 248 | 0.1702 | 0.95 |
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+ | 0.2394 | 32.0 | 256 | 0.0144 | 1.0 |
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+ | 0.1625 | 33.0 | 264 | 0.0145 | 1.0 |
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+ | 0.0999 | 34.0 | 272 | 0.0172 | 1.0 |
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+ | 0.0406 | 35.0 | 280 | 0.0106 | 1.0 |
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+ | 0.0406 | 36.0 | 288 | 0.0098 | 1.0 |
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+ | 0.0374 | 37.0 | 296 | 0.0097 | 1.0 |
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+ | 0.0268 | 38.0 | 304 | 0.0100 | 1.0 |
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+ | 0.0279 | 39.0 | 312 | 0.0111 | 1.0 |
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+ | 0.031 | 40.0 | 320 | 0.0099 | 1.0 |
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+ | 0.031 | 41.0 | 328 | 0.0096 | 1.0 |
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+ | 0.0412 | 42.0 | 336 | 0.0096 | 1.0 |
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+ | 0.0218 | 43.0 | 344 | 0.0087 | 1.0 |
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+ | 0.026 | 44.0 | 352 | 0.0079 | 1.0 |
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+ | 0.0122 | 45.0 | 360 | 0.0081 | 1.0 |
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+ | 0.0122 | 46.0 | 368 | 0.0087 | 1.0 |
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+ | 0.0328 | 47.0 | 376 | 0.0088 | 1.0 |
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+ | 0.0264 | 48.0 | 384 | 0.0084 | 1.0 |
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+ | 0.0339 | 49.0 | 392 | 0.0078 | 1.0 |
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+ | 0.0257 | 50.0 | 400 | 0.0077 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.18.0
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+ - Pytorch 1.11.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.12.1
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