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Wav2Vec2_EmoRecog_Model_v5

Audio Classification
Transformers
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Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
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  1. README.md +80 -0
  2. model.safetensors +1 -1
  3. runs/Dec23_02-14-39_b3ef597b218e/events.out.tfevents.1734920083.b3ef597b218e.3068.5 +2 -2
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-base
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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_EmoRecog_Model_v5
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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_EmoRecog_Model_v5
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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: 1.9448
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+ - Accuracy: 0.4436
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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: 1.5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 20
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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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+ | 1.7312 | 1.0 | 753 | 1.7018 | 0.3267 |
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+ | 1.6018 | 2.0 | 1506 | 1.5855 | 0.3738 |
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+ | 1.5244 | 3.0 | 2259 | 1.5603 | 0.3931 |
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+ | 1.4636 | 4.0 | 3012 | 1.5217 | 0.4017 |
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+ | 1.3947 | 5.0 | 3765 | 1.5199 | 0.4309 |
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+ | 1.3283 | 6.0 | 4518 | 1.5389 | 0.4230 |
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+ | 1.2596 | 7.0 | 5271 | 1.5628 | 0.4250 |
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+ | 1.191 | 8.0 | 6024 | 1.5612 | 0.4555 |
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+ | 1.1193 | 9.0 | 6777 | 1.5749 | 0.4542 |
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+ | 1.0812 | 10.0 | 7530 | 1.6029 | 0.4462 |
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+ | 1.0058 | 11.0 | 8283 | 1.6582 | 0.4422 |
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+ | 0.9441 | 12.0 | 9036 | 1.7178 | 0.4290 |
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+ | 0.8932 | 13.0 | 9789 | 1.7609 | 0.4502 |
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+ | 0.8477 | 14.0 | 10542 | 1.8105 | 0.4469 |
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+ | 0.7997 | 15.0 | 11295 | 1.7957 | 0.4382 |
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+ | 0.7716 | 16.0 | 12048 | 1.8160 | 0.4502 |
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+ | 0.7133 | 17.0 | 12801 | 1.9470 | 0.4329 |
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+ | 0.7034 | 18.0 | 13554 | 1.9191 | 0.4462 |
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+ | 0.6867 | 19.0 | 14307 | 1.9275 | 0.4495 |
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+ | 0.6435 | 20.0 | 15060 | 1.9448 | 0.4436 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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