End of training

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: whisper-tiny-finetuned-gtzan
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: GTZAN
+      type: marsyas/gtzan
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.88
+---
+
+<!-- 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. -->
+
+# whisper-tiny-finetuned-gtzan
+
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8859
+- Accuracy: 0.88
+
+## 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: 5e-05
+- 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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.7103        | 1.0   | 113  | 1.4757          | 0.57     |
+| 0.8805        | 2.0   | 226  | 0.8030          | 0.74     |
+| 0.7231        | 3.0   | 339  | 0.4844          | 0.88     |
+| 0.9119        | 4.0   | 452  | 0.6392          | 0.79     |
+| 0.2952        | 5.0   | 565  | 0.5729          | 0.83     |
+| 0.1099        | 6.0   | 678  | 0.5263          | 0.83     |
+| 0.1363        | 7.0   | 791  | 0.4978          | 0.91     |
+| 0.0021        | 8.0   | 904  | 0.6480          | 0.89     |
+| 0.0413        | 9.0   | 1017 | 0.7381          | 0.87     |
+| 0.0023        | 10.0  | 1130 | 0.6896          | 0.9      |
+| 0.0006        | 11.0  | 1243 | 0.7574          | 0.89     |
+| 0.1621        | 12.0  | 1356 | 0.8407          | 0.88     |
+| 0.0005        | 13.0  | 1469 | 0.7967          | 0.89     |
+| 0.0005        | 14.0  | 1582 | 0.7795          | 0.89     |
+| 0.0004        | 15.0  | 1695 | 0.7795          | 0.9      |
+| 0.0003        | 16.0  | 1808 | 0.9152          | 0.87     |
+| 0.0003        | 17.0  | 1921 | 0.8594          | 0.88     |
+| 0.0003        | 18.0  | 2034 | 0.8481          | 0.88     |
+| 0.0003        | 19.0  | 2147 | 0.8471          | 0.88     |
+| 0.0545        | 20.0  | 2260 | 0.8859          | 0.88     |
+
+
+### Framework versions
+
+- Transformers 4.33.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "openai/whisper-tiny",
+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "apply_spec_augment": false,
+  "architectures": [
+    "WhisperForAudioClassification"
+  ],
+  "attention_dropout": 0.0,
+  "begin_suppress_tokens": [
+    220,
+    50257
+  ],
+  "bos_token_id": 50257,
+  "classifier_proj_size": 256,
+  "d_model": 384,
+  "decoder_attention_heads": 6,
+  "decoder_ffn_dim": 1536,
+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 4,
+  "decoder_start_token_id": 50258,
+  "dropout": 0.0,
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+  "encoder_layerdrop": 0.0,
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+    "3": "disco",
+    "4": "hiphop",
+    "5": "jazz",
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+    "8": "reggae",
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+  "mask_feature_length": 10,
+  "mask_feature_min_masks": 0,
+  "mask_feature_prob": 0.0,
+  "mask_time_length": 10,
+  "mask_time_min_masks": 2,
+  "mask_time_prob": 0.05,
+  "max_length": 448,
+  "max_source_positions": 1500,
+  "max_target_positions": 448,
+  "median_filter_width": 7,
+  "model_type": "whisper",
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+  "torch_dtype": "float32",
+  "transformers_version": "4.33.0.dev0",
+  "use_cache": true,
+  "use_weighted_layer_sum": false,
+  "vocab_size": 51865
+}

preprocessor_config.json

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+{
+  "chunk_length": 30,
+  "feature_extractor_type": "WhisperFeatureExtractor",
+  "feature_size": 80,
+  "hop_length": 160,
+  "n_fft": 400,
+  "n_samples": 480000,
+  "nb_max_frames": 3000,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "processor_class": "WhisperProcessor",
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}

pytorch_model.bin

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training_args.bin

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