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Model: wu-kiot/whisper-small-fc-am
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: wu-kiot/whisper-small-am-fleurs
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_17_0
+metrics:
+- wer
+model-index:
+- name: whisper-small-fc-am
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_17_0
+      type: common_voice_17_0
+      config: am
+      split: None
+      args: am
+    metrics:
+    - name: Wer
+      type: wer
+      value: 62.73062730627307
+---
+
+<!-- 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-fc-am
+
+This model is a fine-tuned version of [wu-kiot/whisper-small-am-fleurs](https://huggingface.co/wu-kiot/whisper-small-am-fleurs) on the common_voice_17_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3756
+- Wer: 62.7306
+
+## 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: 16
+- eval_batch_size: 32
+- 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_steps: 150
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.2866        | 1.0   | 44   | 0.2855          | 63.9958 |
+| 0.1582        | 2.0   | 88   | 0.2958          | 64.1539 |
+| 0.0885        | 3.0   | 132  | 0.3311          | 67.4222 |
+| 0.0793        | 4.0   | 176  | 0.3700          | 66.4207 |
+| 0.0375        | 5.0   | 220  | 0.3756          | 62.7306 |
+
+
+### Framework versions
+
+- Transformers 4.49.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0