Model save

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-base
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_16_0
+metrics:
+- wer
+model-index:
+- name: whisper-base-common-voice-16-pt-v6
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_16_0
+      type: common_voice_16_0
+      config: pt
+      split: test[0:5400]
+      args: pt
+    metrics:
+    - name: Wer
+      type: wer
+      value: 25.542580301884676
+---
+
+<!-- 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-common-voice-16-pt-v6
+
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the common_voice_16_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3952
+- Wer: 25.5426
+- Wer Normalized: 19.7098
+
+## 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: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 400
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     | Wer Normalized |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------------:|
+| 0.5344        | 0.37  | 500  | 0.5264          | 35.9965 | 30.1234        |
+| 0.438         | 0.74  | 1000 | 0.4904          | 33.4453 | 28.3776        |
+| 0.1871        | 1.11  | 1500 | 0.4595          | 30.3929 | 24.5163        |
+| 0.1955        | 1.48  | 2000 | 0.4342          | 28.6566 | 22.9762        |
+| 0.1754        | 1.85  | 2500 | 0.4199          | 28.2674 | 22.4147        |
+| 0.0649        | 2.22  | 3000 | 0.4090          | 26.7860 | 20.7689        |
+| 0.0595        | 2.59  | 3500 | 0.4026          | 26.1839 | 20.2018        |
+| 0.0626        | 2.96  | 4000 | 0.3952          | 25.5426 | 19.7098        |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.1
+- Datasets 2.16.1
+- Tokenizers 0.15.0

generation_config.json

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+}