End of training

README.md

@@ -0,0 +1,83 @@
+---
+language:
+- pl
+license: apache-2.0
+base_model: openai/whisper-large-v3
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_11_0
+metrics:
+- wer
+model-index:
+- name: Whisper Large V3 pl - Chee Li
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 11.0
+      type: mozilla-foundation/common_voice_11_0
+      config: pl
+      split: None
+      args: 'config: pl split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 614.9727204417002
+---
+
+<!-- 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 pl - Chee Li
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 11.0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1865
+- Wer: 614.9727
+
+## 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: 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      |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.1328        | 0.6439 | 1000 | 0.2206          | 275.0400 |
+| 0.0517        | 1.2878 | 2000 | 0.2183          | 668.6775 |
+| 0.0501        | 1.9317 | 3000 | 0.1740          | 468.4439 |
+| 0.022         | 2.5757 | 4000 | 0.1865          | 614.9727 |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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+}

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