End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- generated_from_trainer
+datasets:
+- audiofolder
+metrics:
+- accuracy
+model-index:
+- name: whisper-tiny-tel-tam
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: Speech Commands
+      type: audiofolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9772727272727273
+---
+
+<!-- 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-tel-tam
+
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Speech Commands dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1934
+- Accuracy: 0.9773
+
+## 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 OptimizerNames.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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7009        | 1.0   | 175  | 0.9922          | 0.5227   |
+| 0.024         | 2.0   | 350  | 0.2727          | 0.9091   |
+| 0.4103        | 3.0   | 525  | 0.0223          | 1.0      |
+| 0.0008        | 4.0   | 700  | 0.1908          | 0.9773   |
+| 0.0005        | 5.0   | 875  | 0.1802          | 0.9773   |
+| 0.0005        | 6.0   | 1050 | 0.1826          | 0.9773   |
+| 0.0003        | 7.0   | 1225 | 0.1868          | 0.9773   |
+| 0.0002        | 8.0   | 1400 | 0.1904          | 0.9773   |
+| 0.0003        | 9.0   | 1575 | 0.1925          | 0.9773   |
+| 0.0002        | 10.0  | 1750 | 0.1934          | 0.9773   |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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