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End of training

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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-minds14-audio-classification
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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-minds14-audio-classification
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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: 2.6429
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+ - Accuracy: 0.0912
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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: 4
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 16
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 5
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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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+ | 2.6536 | 0.9945 | 90 | 2.6776 | 0.0442 |
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+ | 2.6478 | 2.0 | 181 | 2.6429 | 0.0912 |
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+ | 2.6354 | 2.9945 | 271 | 2.6509 | 0.0691 |
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+ | 2.648 | 4.0 | 362 | 2.6413 | 0.0414 |
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+ | 2.6401 | 4.9724 | 450 | 2.6199 | 0.0773 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.2
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+ - Pytorch 2.5.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
config.json ADDED
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+ {
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+ "activation_dropout": 0.0,
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+ "apply_spec_augment": true,
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+ "architectures": [
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+ "Wav2Vec2ForSequenceClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "bos_token_id": 1,
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+ "classifier_proj_size": 256,
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+ "codevector_dim": 256,
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+ "contrastive_logits_temperature": 0.1,
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+ "feat_extract_activation": "gelu",
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