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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-conformer-rel-pos-large
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ model-index:
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+ - name: wav2vec2-conformer-rel-pos-large-medical-intent-v2
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+ results:
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+ - task:
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+ name: Audio Classification
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+ type: audio-classification
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+ dataset:
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+ name: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: validation
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.6169590643274854
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+ - name: Precision
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+ type: precision
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+ value: 0.6350528050296339
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+ - name: Recall
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+ type: recall
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+ value: 0.6169590643274854
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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-conformer-rel-pos-large-medical-intent-v2
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-conformer-rel-pos-large](https://huggingface.co/facebook/wav2vec2-conformer-rel-pos-large) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0410
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+ - Accuracy: 0.6170
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+ - Precision: 0.6351
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+ - Recall: 0.6170
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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: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 64
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 4
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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 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
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+ | 1.7714 | 1.0 | 82 | 1.7605 | 0.2339 | 0.3198 | 0.2339 |
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+ | 1.511 | 2.0 | 164 | 1.5148 | 0.4298 | 0.3817 | 0.4298 |
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+ | 1.1417 | 2.99 | 246 | 1.1530 | 0.5936 | 0.6491 | 0.5936 |
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+ | 0.8747 | 3.99 | 328 | 1.0410 | 0.6170 | 0.6351 | 0.6170 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.1
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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