End of training

README.md

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+---
+language:
+- en
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: Whisper small v5-en finetuned
+  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 small v5-en finetuned
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the my_audio_dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1560
+- Wer: 5.6915
+
+## 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
+- 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: 300
+- training_steps: 3000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Wer    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|
+| 0.1138        | 5.8309  | 1000 | 0.1326          | 6.3035 |
+| 0.004         | 11.6618 | 2000 | 0.1507          | 5.7015 |
+| 0.0014        | 17.4927 | 3000 | 0.1560          | 5.6915 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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+}