End of training

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- generated_from_trainer
+datasets:
+- speech_commands
+metrics:
+- accuracy
+model-index:
+- name: whisper-tiny-speech-commands
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: speech_commands
+      type: speech_commands
+      config: v0.02
+      split: None
+      args: v0.02
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8039568345323741
+---
+
+<!-- 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-speech-commands
+
+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: 1.3232
+- Accuracy: 0.8040
+
+## 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: 96
+- eval_batch_size: 96
+- 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: 20
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4229        | 1.0   | 412  | 1.1286          | 0.7936   |
+| 0.1396        | 2.0   | 824  | 1.0506          | 0.7995   |
+| 0.1323        | 3.0   | 1236 | 1.1224          | 0.7977   |
+| 0.0528        | 4.0   | 1648 | 1.0810          | 0.8004   |
+| 0.0889        | 5.0   | 2060 | 0.9224          | 0.8022   |
+| 0.076         | 6.0   | 2472 | 1.0393          | 0.7981   |
+| 0.0429        | 7.0   | 2884 | 1.1115          | 0.7990   |
+| 0.0007        | 8.0   | 3296 | 1.1706          | 0.8026   |
+| 0.0129        | 9.0   | 3708 | 1.0661          | 0.8013   |
+| 0.0161        | 10.0  | 4120 | 1.0114          | 0.7990   |
+| 0.0205        | 11.0  | 4532 | 1.2129          | 0.8031   |
+| 0.0107        | 12.0  | 4944 | 1.1118          | 0.8026   |
+| 0.0099        | 13.0  | 5356 | 0.9145          | 0.8031   |
+| 0.0002        | 14.0  | 5768 | 1.1582          | 0.7999   |
+| 0.0001        | 15.0  | 6180 | 1.2959          | 0.8035   |
+| 0.0163        | 16.0  | 6592 | 1.0992          | 0.8026   |
+| 0.0001        | 17.0  | 7004 | 1.2913          | 0.8035   |
+| 0.0003        | 18.0  | 7416 | 1.3232          | 0.8040   |
+| 0.0001        | 19.0  | 7828 | 1.3720          | 0.8040   |
+| 0.0001        | 20.0  | 8240 | 1.3889          | 0.8040   |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.2.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.1

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runs/Oct01_11-56-20_ki-g0010/events.out.tfevents.1727786124.ki-g0010.1593563.1

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