初始化项目，由ModelHub XC社区提供模型

Model: IonGrozea/whisper-medium_ro-80mel
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: openai/whisper-medium
+tags:
+- generated_from_trainer
+datasets:
+- generator
+metrics:
+- wer
+model-index:
+- name: whisper-medium_ro-80mel
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: generator
+      type: generator
+      config: default
+      split: None
+      args: default
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.6935
+---
+
+<!-- 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_ro-80mel
+
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the generator dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0839
+- Wer: 0.6935
+- Cer: 1.202
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 64
+- total_train_batch_size: 64
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Cer    | Validation Loss | Wer    |
+|:-------------:|:------:|:-----:|:------:|:---------------:|:------:|
+| 0.1665        | 0.7723 | 2500  | 0.9148 | 0.0839          | 0.7855 |
+| 0.108         | 1.5443 | 5000  | 2.035  | 0.0722          | 2.1169 |
+| 0.0805        | 2.3163 | 7500  | 2.5247 | 0.0718          | 2.4453 |
+| 0.0589        | 3.0883 | 10000 | 2.8635 | 0.0583          | 2.8751 |
+| 0.0516        | 3.8606 | 12500 | 3.1281 | 0.0511          | 3.2984 |
+| 0.0415        | 4.6326 | 15000 | 3.2897 | 0.0540          | 3.365  |
+| 0.0368        | 5.4047 | 17500 | 0.0543 | 3.4251          | 3.298  |
+| 0.0315        | 6.1767 | 20000 | 0.0559 | 3.2634          | 3.2452 |
+| 0.0316        | 6.9490 | 22500 | 0.0541 | 3.6173          | 3.4674 |
+| 0.0267        | 7.7210 | 25000 | 0.0547 | 3.3599          | 3.2115 |
+
+"eval_runtime": 113429.374,
+"eval_samples": 27174,
+"eval_samples_per_second": 0.24,
+"eval_steps_per_second": 0.24,
+"test_samples": 12987,
+"train_samples": 207181
+    
+### Framework versions
+
+- Transformers 4.57.0
+- Pytorch 2.9.1+cu128
+- Datasets 4.4.1
+- Tokenizers 0.22.1