Model save

README.md

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+---
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+datasets:
+- audiofolder
+metrics:
+- accuracy
+model-index:
+- name: distilhubert-finetuned-RHD_Dataset
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: audiofolder
+      type: audiofolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8048780487804879
+---
+
+<!-- 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. -->
+
+# distilhubert-finetuned-RHD_Dataset
+
+This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9447
+- Accuracy: 0.8049
+
+## 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: 0.0001
+- 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: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.0412        | 1.0   | 46   | 1.0084          | 0.6829   |
+| 0.8547        | 2.0   | 92   | 0.8433          | 0.6585   |
+| 0.7936        | 3.0   | 138  | 0.7128          | 0.7073   |
+| 0.5984        | 4.0   | 184  | 0.7778          | 0.7317   |
+| 0.3888        | 5.0   | 230  | 0.6361          | 0.7317   |
+| 0.4947        | 6.0   | 276  | 0.7471          | 0.7805   |
+| 0.1663        | 7.0   | 322  | 0.8244          | 0.7561   |
+| 0.1379        | 8.0   | 368  | 0.7986          | 0.8049   |
+| 0.0405        | 9.0   | 414  | 0.8892          | 0.8049   |
+| 0.0229        | 10.0  | 460  | 0.9447          | 0.8049   |
+
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

model.safetensors

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