End of training

README.md

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+---
+language:
+- vi
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: openai/whisper-small
+datasets:
+- stevehoang9/vietnamese_ASR
+metrics:
+- wer
+model-index:
+- name: Whisper Small Vietnam - Steve Hoang
+  results:
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: VIVOS
+      type: stevehoang9/vietnamese_ASR
+    metrics:
+    - type: wer
+      value: 51.68350168350169
+      name: Wer
+---
+
+<!-- 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 Small Vietnam - Steve Hoang
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the VIVOS dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6333
+- Wer: 51.6835
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- 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     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.931         | 1.3717 | 1000 | 0.9599          | 74.7216 |
+| 0.7286        | 2.7435 | 2000 | 0.7709          | 61.5255 |
+| 0.6341        | 4.1152 | 3000 | 0.6854          | 55.5685 |
+| 0.6044        | 5.4870 | 4000 | 0.6458          | 52.8490 |
+| 0.6031        | 6.8587 | 5000 | 0.6333          | 51.6835 |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

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