unanam/whisper-large-ver3

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-large-v2
+tags:
+- generated_from_trainer
+model-index:
+- name: finetuning_dog
+  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. -->
+
+# finetuning_dog
+
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2932
+- Cer: 8.8686
+
+## 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-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Cer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.0863        | 2.76  | 1000 | 0.2303          | 9.1216 |
+| 0.0154        | 5.52  | 2000 | 0.2505          | 8.6437 |
+| 0.002         | 8.29  | 3000 | 0.2877          | 8.6297 |
+| 0.0021        | 11.05 | 4000 | 0.2932          | 8.8686 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.0.0
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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+}

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