End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: arbml/whisper-tiny-ar
+tags:
+- generated_from_trainer
+datasets:
+- speech_commands
+metrics:
+- accuracy
+model-index:
+- name: whisper-tiny-ar-ft-kws-speech-commands
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: Speech Commands
+      type: speech_commands
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.5204081632653061
+---
+
+<!-- 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. -->
+
+# whisper-tiny-ar-ft-kws-speech-commands
+
+This model is a fine-tuned version of [arbml/whisper-tiny-ar](https://huggingface.co/arbml/whisper-tiny-ar) on the Speech Commands dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8423
+- Accuracy: 0.5204
+
+## 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: 2
+- eval_batch_size: 2
+- 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: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.6826        | 1.0   | 1325  | 0.7084          | 0.4966   |
+| 0.7052        | 2.0   | 2650  | 0.6965          | 0.5      |
+| 0.7409        | 3.0   | 3975  | 0.6876          | 0.5510   |
+| 0.7077        | 4.0   | 5300  | 0.7214          | 0.5170   |
+| 0.7988        | 5.0   | 6625  | 0.7523          | 0.4898   |
+| 0.5818        | 6.0   | 7950  | 0.8118          | 0.5510   |
+| 0.7722        | 7.0   | 9275  | 0.9102          | 0.5306   |
+| 1.4165        | 8.0   | 10600 | 1.6832          | 0.5      |
+| 0.7113        | 9.0   | 11925 | 1.6268          | 0.5340   |
+| 0.2578        | 10.0  | 13250 | 1.8423          | 0.5204   |
+
+
+### Framework versions
+
+- Transformers 4.48.0.dev0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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