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End of training

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README.md ADDED
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - speech_commands
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: wav2vec2-speechcommonds-kws
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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: speech_commands
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+ type: speech_commands
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+ config: v0.02
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+ split: test
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+ args: v0.02
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9854975457385096
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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-speechcommonds-kws
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+
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+ This model was trained from scratch on the speech_commands dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0613
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+ - Accuracy: 0.9855
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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: 3e-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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 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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+ | 1.0871 | 1.0 | 741 | 0.3374 | 0.9810 |
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+ | 0.5168 | 2.0 | 1482 | 0.1022 | 0.9866 |
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+ | 0.4113 | 3.0 | 2223 | 0.0766 | 0.9853 |
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+ | 0.3622 | 4.0 | 2964 | 0.0670 | 0.9859 |
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+ | 0.3454 | 5.0 | 3705 | 0.0613 | 0.9855 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.1
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+ - Pytorch 2.1.1
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
config.json ADDED
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+ "_name_or_path": "D:/AudioClassification/wav2vec2-large-960h-lv60",
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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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+ "codevector_dim": 256,
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+ "do_stable_layer_norm": true,
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+ "feat_extract_activation": "gelu",
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+ "id2label": {
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+ "0": "yes",
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+ "10": "zero",
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+ "11": "one",
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+ "12": "two",
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+ "16": "six",
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+ "17": "seven",
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+ "18": "eight",
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+ "19": "nine",
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+ "2": "up",
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+ "20": "bed",
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+ "21": "bird",
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+ "22": "cat",
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+ "23": "dog",
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+ "24": "happy",
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+ "25": "house",
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+ "26": "marvin",
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+ "27": "sheila",
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+ "28": "tree",
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+ "3": "down",
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+ "layer_norm_eps": 1e-05,
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+ "num_adapter_layers": 3,
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