End of training

README.md

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+---
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+datasets:
+- birdclef/hubert
+metrics:
+- accuracy
+model-index:
+- name: distilhubert-finetuned-birdclef
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: Birdclef 2024
+      type: birdclef/hubert
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6974652493867539
+---
+
+<!-- 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-birdclef
+
+This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the Birdclef 2024 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8592
+- Accuracy: 0.6975
+- F1 Macro: 0.4507
+- F1 Weighted: 0.6871
+
+## 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 | F1 Macro | F1 Weighted |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------:|
+| 3.3212        | 1.0   | 2446  | 3.4889          | 0.2343   | 0.0453   | 0.1567      |
+| 2.5841        | 2.0   | 4892  | 2.1989          | 0.5123   | 0.1673   | 0.4489      |
+| 1.5152        | 3.0   | 7338  | 1.8349          | 0.5871   | 0.2449   | 0.5452      |
+| 1.4771        | 4.0   | 9784  | 1.6815          | 0.6300   | 0.3213   | 0.6048      |
+| 1.0287        | 5.0   | 12230 | 1.6218          | 0.6627   | 0.3498   | 0.6462      |
+| 0.9425        | 6.0   | 14676 | 1.6177          | 0.6688   | 0.3835   | 0.6511      |
+| 0.291         | 7.0   | 17122 | 1.7205          | 0.6832   | 0.3903   | 0.6682      |
+| 0.244         | 8.0   | 19568 | 1.7817          | 0.6811   | 0.4049   | 0.6706      |
+| 0.0593        | 9.0   | 22014 | 1.8653          | 0.6881   | 0.4282   | 0.6755      |
+| 0.0754        | 10.0  | 24460 | 1.8877          | 0.6917   | 0.4320   | 0.6823      |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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