End of training

README.md

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+---
+language:
+- en
+license: apache-2.0
+base_model: openai/whisper-base
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: Whisper Small Five - Chee Li
+  results: []
+---
+
+<!-- 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 Five - Chee Li
+
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Google Fleurs dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4348
+- Wer: 21.6569
+
+## 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: 850
+- training_steps: 8000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.3047        | 1.0560 | 1000 | 0.4050          | 22.7955 |
+| 0.1771        | 2.1119 | 2000 | 0.3811          | 21.0509 |
+| 0.1176        | 3.1679 | 3000 | 0.3864          | 21.3429 |
+| 0.0852        | 4.2239 | 4000 | 0.3962          | 20.7720 |
+| 0.0443        | 5.2798 | 5000 | 0.4100          | 21.4523 |
+| 0.0265        | 6.3358 | 6000 | 0.4234          | 21.3823 |
+| 0.0254        | 7.3918 | 7000 | 0.4310          | 21.7783 |
+| 0.0188        | 8.4477 | 8000 | 0.4348          | 21.6569 |
+
+
+### Framework versions
+
+- Transformers 4.43.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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+}

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