End of training

README.md

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+---
+language:
+- ms
+license: apache-2.0
+base_model: openai/whisper-medium
+tags:
+- generated_from_trainer
+datasets:
+- clt013/malay-speech-1.6-million-rows-dataset
+metrics:
+- wer
+model-index:
+- name: Whisper Medium FT Malay - CLT013
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Malay Speech 1.6 million
+      type: clt013/malay-speech-1.6-million-rows-dataset
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Wer
+      type: wer
+      value: 33.069727071077246
+---
+
+<!-- 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 Medium FT Malay - CLT013
+
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Malay Speech 1.6 million dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5227
+- Wer: 33.0697
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 5000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.6896        | 0.2   | 1000 | 0.7044          | 40.9683 |
+| 0.634         | 0.4   | 2000 | 0.6366          | 40.5439 |
+| 0.5836        | 0.6   | 3000 | 0.5821          | 34.3331 |
+| 0.5568        | 0.8   | 4000 | 0.5446          | 33.6870 |
+| 0.535         | 1.0   | 5000 | 0.5227          | 33.0697 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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