eeem069_ast_murmur

README.md

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+---
+license: bsd-3-clause
+base_model: MIT/ast-finetuned-audioset-10-10-0.4593
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: exp_1715025412
+  results: []
+---
+
+<!-- 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. -->
+
+# exp_1715025412
+
+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 an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6403
+- Accuracy: 0.8974
+
+## 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: 3e-05
+- train_batch_size: 12
+- eval_batch_size: 12
+- seed: 42
+- gradient_accumulation_steps: 5
+- total_train_batch_size: 60
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.5131        | 0.9856 | 41   | 0.4401          | 0.8157   |
+| 0.2645        | 1.9952 | 83   | 0.3510          | 0.875    |
+| 0.2224        | 2.9808 | 124  | 0.3333          | 0.8910   |
+| 0.1223        | 3.9904 | 166  | 0.4310          | 0.8830   |
+| 0.0721        | 5.0    | 208  | 0.5080          | 0.8830   |
+| 0.0059        | 5.9856 | 249  | 0.6021          | 0.8910   |
+| 0.001         | 6.9952 | 291  | 0.6082          | 0.8878   |
+| 0.0004        | 7.9808 | 332  | 0.6385          | 0.8942   |
+| 0.0002        | 8.9904 | 374  | 0.6386          | 0.8958   |
+| 0.0003        | 9.8558 | 410  | 0.6403          | 0.8974   |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- 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": "Absent",
+    "1": "Present",
+    "2": "Unknown"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Absent": "0",
+    "Present": "1",
+    "Unknown": "2"
+  },
+  "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": "4.40.1"
+}

model.safetensors

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+oid sha256:1bd62c1bc7019aeb5bdffd7eb3c2ecee967184db533ad38bbadb22cf9866be13
+size 344793116

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "feature_extractor_type": "ASTFeatureExtractor",
+  "feature_size": 1,
+  "max_length": 1024,
+  "mean": -4.2677393,
+  "num_mel_bins": 128,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "return_attention_mask": false,
+  "sampling_rate": 16000,
+  "std": 4.5689974
+}

runs/May06_19-57-43_bc4080cc2048/events.out.tfevents.1715025473.bc4080cc2048.1769.0

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+size 25587

training_args.bin

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