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Wav2Vec2_EmoRecog_Model_v2

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
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  1. README.md +80 -0
  2. model.safetensors +1 -1
  3. runs/Dec23_00-10-03_b3ef597b218e/events.out.tfevents.1734912606.b3ef597b218e.3068.0 +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_v2
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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_v2
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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: 1.8440
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+ - Accuracy: 0.4349
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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: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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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+ | 1.7698 | 1.0 | 377 | 1.6608 | 0.3513 |
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+ | 1.6102 | 2.0 | 754 | 1.6074 | 0.3625 |
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+ | 1.5556 | 3.0 | 1131 | 1.5894 | 0.3778 |
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+ | 1.4899 | 4.0 | 1508 | 1.5643 | 0.3858 |
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+ | 1.4322 | 5.0 | 1885 | 1.5250 | 0.4084 |
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+ | 1.3737 | 6.0 | 2262 | 1.5445 | 0.4110 |
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+ | 1.3217 | 7.0 | 2639 | 1.5287 | 0.4210 |
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+ | 1.2686 | 8.0 | 3016 | 1.5635 | 0.4243 |
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+ | 1.1999 | 9.0 | 3393 | 1.5674 | 0.4223 |
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+ | 1.1511 | 10.0 | 3770 | 1.5881 | 0.4363 |
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+ | 1.087 | 11.0 | 4147 | 1.6162 | 0.4177 |
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+ | 1.0309 | 12.0 | 4524 | 1.6487 | 0.4296 |
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+ | 0.9778 | 13.0 | 4901 | 1.7363 | 0.4210 |
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+ | 0.9344 | 14.0 | 5278 | 1.7568 | 0.4210 |
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+ | 0.9108 | 15.0 | 5655 | 1.7051 | 0.4416 |
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+ | 0.8449 | 16.0 | 6032 | 1.7945 | 0.4329 |
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+ | 0.8268 | 17.0 | 6409 | 1.7778 | 0.4402 |
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+ | 0.7991 | 18.0 | 6786 | 1.7972 | 0.4382 |
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+ | 0.7604 | 19.0 | 7163 | 1.8238 | 0.4276 |
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+ | 0.7329 | 20.0 | 7540 | 1.8440 | 0.4349 |
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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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