End of training

README.md

@@ -0,0 +1,86 @@
+---
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+datasets:
+- narad/ravdess
+metrics:
+- accuracy
+model-index:
+- name: distilhubert-finetuned-ravdess
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: RAVDESS
+      type: narad/ravdess
+      config: all
+      split: train
+      args: all
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8194444444444444
+---
+
+<!-- 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-ravdess
+
+This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the RAVDESS dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6720
+- Accuracy: 0.8194
+
+## 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: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.795         | 1.0   | 162  | 1.8129          | 0.25     |
+| 1.1416        | 2.0   | 324  | 1.2499          | 0.5278   |
+| 1.1677        | 3.0   | 486  | 0.9141          | 0.6875   |
+| 0.5474        | 4.0   | 648  | 0.7662          | 0.75     |
+| 0.4129        | 5.0   | 810  | 0.6744          | 0.7569   |
+| 0.2396        | 6.0   | 972  | 0.6781          | 0.7986   |
+| 0.0626        | 7.0   | 1134 | 0.7809          | 0.75     |
+| 0.1198        | 8.0   | 1296 | 0.6404          | 0.8194   |
+| 0.0187        | 9.0   | 1458 | 0.6750          | 0.8264   |
+| 0.012         | 10.0  | 1620 | 0.6720          | 0.8194   |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1
+- Datasets 2.19.1
+- Tokenizers 0.19.1

model.safetensors

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