End of training

README.md

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+---
+language:
+- rus
+license: apache-2.0
+base_model: openai/whisper-large-v3
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: Whisper Large V3 rus pl - Chee Li
+  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 Large V3 rus pl - Chee Li
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Google Fleurs dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1165
+- Wer: 108.0475
+
+## 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-06
+- 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: 500
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Wer      |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 0.0324        | 2.6178  | 1000 | 0.0814          | 73.6269  |
+| 0.0058        | 5.2356  | 2000 | 0.1047          | 117.0652 |
+| 0.0033        | 7.8534  | 3000 | 0.1141          | 126.9367 |
+| 0.0022        | 10.4712 | 4000 | 0.1165          | 108.0475 |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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