Model save

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- recall
+- precision
+model-index:
+- name: whisper-base-finetuned-common_voice
+  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-base-finetuned-common_voice
+
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0319
+- Accuracy: 0.9925
+- F1: 0.9925
+- Recall: 0.9925
+- Precision: 0.9927
+- Mcc: 0.9907
+- Auc: 0.9999
+
+## 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: 8
+- 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_ratio: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision | Mcc    | Auc    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
+| 0.1765        | 1.0   | 200  | 0.1455          | 0.9775   | 0.9775 | 0.9775 | 0.9776    | 0.9719 | 0.9996 |
+| 0.0067        | 2.0   | 400  | 0.0734          | 0.98     | 0.9800 | 0.9800 | 0.9804    | 0.9751 | 0.9996 |
+| 0.0218        | 3.0   | 600  | 0.0719          | 0.9875   | 0.9875 | 0.9875 | 0.9879    | 0.9845 | 0.9999 |
+| 0.002         | 4.0   | 800  | 0.1055          | 0.975    | 0.9752 | 0.975  | 0.9762    | 0.9690 | 0.9997 |
+| 0.0014        | 5.0   | 1000 | 0.0312          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9999 |
+| 0.0011        | 6.0   | 1200 | 0.0305          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9999 |
+| 0.0009        | 7.0   | 1400 | 0.0310          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9999 |
+| 0.0008        | 8.0   | 1600 | 0.0315          | 0.9925   | 0.9925 | 0.9925 | 0.9927    | 0.9907 | 0.9999 |
+| 0.0008        | 9.0   | 1800 | 0.0318          | 0.9925   | 0.9925 | 0.9925 | 0.9927    | 0.9907 | 0.9999 |
+| 0.0007        | 10.0  | 2000 | 0.0319          | 0.9925   | 0.9925 | 0.9925 | 0.9927    | 0.9907 | 0.9999 |
+
+
+### Framework versions
+
+- Transformers 4.41.0
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

model.safetensors

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