Training in progress, epoch 10
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README.md
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---
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license: apache-2.0
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base_model: ntu-spml/distilhubert
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tags:
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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metrics:
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- accuracy
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model-index:
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- name: distilhubert-finetuned-gtzan-v3
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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: GTZAN
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type: marsyas/gtzan
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.86
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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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# distilhubert-finetuned-gtzan-v3
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1337
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- Accuracy: 0.86
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 1
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- eval_batch_size: 1
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- seed: 42
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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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- num_epochs: 10
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.7102 | 1.0 | 899 | 0.9058 | 0.69 |
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| 1.9987 | 2.0 | 1798 | 1.3215 | 0.71 |
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| 0.0086 | 3.0 | 2697 | 0.9701 | 0.75 |
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| 0.0284 | 4.0 | 3596 | 0.8695 | 0.82 |
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| 0.1668 | 5.0 | 4495 | 1.1303 | 0.81 |
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| 0.0013 | 6.0 | 5394 | 1.0664 | 0.84 |
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| 0.0026 | 7.0 | 6293 | 1.0936 | 0.87 |
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| 0.0003 | 8.0 | 7192 | 1.1882 | 0.86 |
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| 0.0004 | 9.0 | 8091 | 1.2463 | 0.85 |
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| 0.0002 | 10.0 | 8990 | 1.1337 | 0.86 |
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### Framework versions
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- Transformers 4.44.0
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- Pytorch 2.1.1+cu118
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "ntu-spml/distilhubert",
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"activation_dropout": 0.3,
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"apply_spec_augment": false,
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"architectures": [
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"HubertForSequenceClassification"
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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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"conv_bias": false,
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"conv_dim": [
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512,
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512,
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512,
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512,
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512,
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512,
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512
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],
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"conv_kernel": [
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10,
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],
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"conv_stride": [
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5,
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],
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"ctc_loss_reduction": "sum",
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"ctc_zero_infinity": false,
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"do_stable_layer_norm": false,
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"eos_token_id": 2,
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"feat_extract_activation": "gelu",
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"feat_extract_norm": "group",
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"feat_proj_dropout": 0.0,
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"feat_proj_layer_norm": false,
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"final_dropout": 0.0,
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"hidden_act": "gelu",
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"hidden_dropout": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "blues",
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"1": "classical",
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"2": "country",
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"3": "disco",
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"4": "hiphop",
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"5": "jazz",
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"6": "metal",
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"7": "pop",
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"8": "reggae",
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"9": "rock"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"blues": "0",
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"classical": "1",
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"country": "2",
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"disco": "3",
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"hiphop": "4",
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"jazz": "5",
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"metal": "6",
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"pop": "7",
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"reggae": "8",
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"rock": "9"
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},
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"layer_norm_eps": 1e-05,
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"layerdrop": 0.0,
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"mask_feature_length": 10,
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"mask_feature_min_masks": 0,
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"mask_feature_prob": 0.0,
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"mask_time_length": 10,
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"mask_time_min_masks": 2,
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"mask_time_prob": 0.05,
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"model_type": "hubert",
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"num_attention_heads": 12,
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"num_conv_pos_embedding_groups": 16,
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"num_conv_pos_embeddings": 128,
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"num_feat_extract_layers": 7,
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"num_hidden_layers": 2,
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"pad_token_id": 0,
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"torch_dtype": "float32",
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"transformers_version": "4.44.0",
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"use_weighted_layer_sum": false,
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"vocab_size": 32
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}
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model.safetensors
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preprocessor_config.json
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"feature_extractor_type": "Wav2Vec2FeatureExtractor",
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0,
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"return_attention_mask": true,
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"sampling_rate": 16000
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