End of training

README.md

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+---
+library_name: transformers
+license: bsd-3-clause
+base_model: MIT/ast-finetuned-speech-commands-v2
+tags:
+- generated_from_trainer
+datasets:
+- audiofolder
+metrics:
+- precision
+- recall
+- f1
+model-index:
+- name: ast-finetuned-speech-commands-v2-finetuned-keyword-spotting-finetuned-keyword-spotting
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: audiofolder
+      type: audiofolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9861935383961439
+    - name: Recall
+      type: recall
+      value: 0.9861649413727126
+    - name: F1
+      type: f1
+      value: 0.9861100898918743
+---
+
+<!-- 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. -->
+
+# ast-finetuned-speech-commands-v2-finetuned-keyword-spotting-finetuned-keyword-spotting
+
+This model is a fine-tuned version of [MIT/ast-finetuned-speech-commands-v2](https://huggingface.co/MIT/ast-finetuned-speech-commands-v2) on the audiofolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0685
+- Precision: 0.9862
+- Recall: 0.9862
+- F1: 0.9861
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
+| 0.0682        | 1.0   | 1630 | 0.0976          | 0.9752    | 0.9751 | 0.9749 |
+| 0.0179        | 2.0   | 3260 | 0.0743          | 0.9847    | 0.9846 | 0.9846 |
+| 0.0008        | 3.0   | 4890 | 0.0685          | 0.9862    | 0.9862 | 0.9861 |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.7.0+cu128
+- Datasets 3.6.0
+- Tokenizers 0.21.1