End of training

README.md

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+---
+library_name: transformers
+license: bsd-3-clause
+base_model: MIT/ast-finetuned-audioset-10-10-0.4593
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: ast-finetuned-gtzan
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: GTZAN
+      type: marsyas/gtzan
+      config: all
+      split: train
+      args: all
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.87
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# ast-finetuned-gtzan
+
+This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3848
+- Accuracy: 0.87
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.8911        | 1.0   | 113  | 1.7770          | 0.52     |
+| 0.9154        | 2.0   | 226  | 0.8861          | 0.77     |
+| 0.5408        | 3.0   | 339  | 0.5815          | 0.83     |
+| 0.3854        | 4.0   | 452  | 0.5075          | 0.86     |
+| 0.4656        | 5.0   | 565  | 0.4716          | 0.87     |
+| 0.3679        | 6.0   | 678  | 0.4578          | 0.87     |
+| 0.3263        | 7.0   | 791  | 0.4368          | 0.87     |
+| 0.4072        | 8.0   | 904  | 0.4078          | 0.88     |
+| 0.2734        | 9.0   | 1017 | 0.3847          | 0.88     |
+| 0.3517        | 10.0  | 1130 | 0.4185          | 0.88     |
+| 0.3147        | 11.0  | 1243 | 0.3946          | 0.86     |
+| 0.2572        | 12.0  | 1356 | 0.3899          | 0.88     |
+| 0.3696        | 13.0  | 1469 | 0.3843          | 0.87     |
+| 0.256         | 14.0  | 1582 | 0.3872          | 0.87     |
+| 0.3737        | 15.0  | 1695 | 0.3914          | 0.88     |
+| 0.1702        | 16.0  | 1808 | 0.3863          | 0.87     |
+| 0.2974        | 17.0  | 1921 | 0.3857          | 0.87     |
+| 0.1916        | 18.0  | 2034 | 0.3855          | 0.87     |
+| 0.223         | 19.0  | 2147 | 0.3848          | 0.87     |
+| 0.1942        | 20.0  | 2260 | 0.3848          | 0.87     |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "MIT/ast-finetuned-audioset-10-10-0.4593",
+  "architectures": [
+    "ASTForAudioClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "frequency_stride": 10,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "blues",
+    "1": "classical",
+    "2": "country",
+    "3": "disco",
+    "4": "hiphop",
+    "5": "jazz",
+    "6": "metal",
+    "7": "pop",
+    "8": "reggae",
+    "9": "rock"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "blues": "0",
+    "classical": "1",
+    "country": "2",
+    "disco": "3",
+    "hiphop": "4",
+    "jazz": "5",
+    "metal": "6",
+    "pop": "7",
+    "reggae": "8",
+    "rock": "9"
+  },
+  "layer_norm_eps": 1e-12,
+  "max_length": 1024,
+  "model_type": "audio-spectrogram-transformer",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "num_mel_bins": 128,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "time_stride": 10,
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2"
+}

model.safetensors

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+size 344814656

training_args.bin

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