Model save

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-large-v2
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_13_0
+metrics:
+- wer
+model-index:
+- name: openai/whisper-large-v2
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_13_0
+      type: common_voice_13_0
+      config: eu
+      split: validation
+      args: eu
+    metrics:
+    - name: Wer
+      type: wer
+      value: 12.627697515565494
+---
+
+<!-- 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. -->
+
+# openai/whisper-large-v2
+
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_13_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4121
+- Wer: 12.6277
+
+## 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: 32
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 20000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
+|:-------------:|:------:|:-----:|:---------------:|:-------:|
+| 0.1098        | 5.85   | 1000  | 0.2495          | 16.6354 |
+| 0.022         | 11.7   | 2000  | 0.2733          | 14.6306 |
+| 0.0089        | 17.54  | 3000  | 0.3075          | 13.9697 |
+| 0.0056        | 23.39  | 4000  | 0.3206          | 14.0724 |
+| 0.0053        | 29.24  | 5000  | 0.3314          | 13.7944 |
+| 0.0037        | 35.09  | 6000  | 0.3376          | 13.7480 |
+| 0.0027        | 40.94  | 7000  | 0.3492          | 13.6815 |
+| 0.0023        | 46.78  | 8000  | 0.3455          | 13.8488 |
+| 0.002         | 52.63  | 9000  | 0.3500          | 13.5123 |
+| 0.0009        | 58.48  | 10000 | 0.3590          | 13.2967 |
+| 0.0016        | 64.33  | 11000 | 0.3675          | 13.4679 |
+| 0.0007        | 70.18  | 12000 | 0.3785          | 13.2685 |
+| 0.0008        | 76.02  | 13000 | 0.3822          | 13.3652 |
+| 0.0004        | 81.87  | 14000 | 0.3929          | 13.3148 |
+| 0.0006        | 87.72  | 15000 | 0.3880          | 13.1032 |
+| 0.0002        | 93.57  | 16000 | 0.4005          | 12.6982 |
+| 0.0002        | 99.42  | 17000 | 0.4004          | 13.1516 |
+| 0.0001        | 105.26 | 18000 | 0.4140          | 12.8735 |
+| 0.0001        | 111.11 | 19000 | 0.4131          | 12.5128 |
+| 0.0001        | 116.96 | 20000 | 0.4121          | 12.6277 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

generation_config.json

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+}

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