Training in progress, step 50001

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: whisper-tiny-javanese-openslr-v5
+  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-tiny-javanese-openslr-v5
+
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2530
+- Wer: 0.1763
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 50000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
+|:-------------:|:-------:|:-----:|:---------------:|:------:|
+| 1.0859        | 0.4325  | 1000  | 0.9075          | 0.6419 |
+| 0.7132        | 0.8651  | 2000  | 0.6100          | 0.5481 |
+| 0.5258        | 1.2976  | 3000  | 0.4822          | 0.6352 |
+| 0.4521        | 1.7301  | 4000  | 0.4058          | 0.4619 |
+| 0.3848        | 1.0813  | 5000  | 0.4022          | 0.3778 |
+| 0.351         | 1.2976  | 6000  | 0.3711          | 0.3326 |
+| 0.3277        | 1.5138  | 7000  | 0.3546          | 0.3053 |
+| 0.3122        | 1.7301  | 8000  | 0.3370          | 0.2862 |
+| 0.3433        | 1.9464  | 9000  | 0.3173          | 0.2501 |
+| 0.2336        | 2.1626  | 10000 | 0.3144          | 0.2563 |
+| 0.2238        | 2.3789  | 11000 | 0.3043          | 0.2355 |
+| 0.2225        | 2.5952  | 12000 | 0.2969          | 0.2403 |
+| 0.218         | 2.8114  | 13000 | 0.2881          | 0.2326 |
+| 0.1778        | 3.0277  | 14000 | 0.2848          | 0.2142 |
+| 0.1669        | 3.2439  | 15000 | 0.2824          | 0.2114 |
+| 0.1621        | 3.4602  | 16000 | 0.2812          | 0.2131 |
+| 0.1585        | 3.6765  | 17000 | 0.2753          | 0.2114 |
+| 0.1567        | 3.8927  | 18000 | 0.2723          | 0.1973 |
+| 0.1092        | 4.1090  | 19000 | 0.2706          | 0.2005 |
+| 0.1122        | 4.3253  | 20000 | 0.2704          | 0.2092 |
+| 0.1138        | 4.5415  | 21000 | 0.2706          | 0.1959 |
+| 0.121         | 4.7578  | 22000 | 0.2650          | 0.1952 |
+| 0.11          | 4.9740  | 23000 | 0.2642          | 0.1935 |
+| 0.0848        | 5.1903  | 24000 | 0.2655          | 0.1916 |
+| 0.0844        | 5.4066  | 25000 | 0.2644          | 0.1890 |
+| 0.0836        | 5.6228  | 26000 | 0.2626          | 0.1905 |
+| 0.087         | 5.8391  | 27000 | 0.2587          | 0.1885 |
+| 0.059         | 6.0554  | 28000 | 0.2594          | 0.1827 |
+| 0.0596        | 6.2716  | 29000 | 0.2606          | 0.1835 |
+| 0.0616        | 6.4879  | 30000 | 0.2587          | 0.1895 |
+| 0.0634        | 6.7042  | 31000 | 0.2577          | 0.1805 |
+| 0.0647        | 6.9204  | 32000 | 0.2557          | 0.1859 |
+| 0.0467        | 7.1367  | 33000 | 0.2584          | 0.1800 |
+| 0.0474        | 7.3529  | 34000 | 0.2545          | 0.1800 |
+| 0.0478        | 7.5692  | 35000 | 0.2588          | 0.1827 |
+| 0.0485        | 7.7855  | 36000 | 0.2559          | 0.1800 |
+| 0.0456        | 8.0017  | 37000 | 0.2556          | 0.1804 |
+| 0.0361        | 8.2180  | 38000 | 0.2560          | 0.1844 |
+| 0.0354        | 8.4343  | 39000 | 0.2550          | 0.1806 |
+| 0.0365        | 8.6505  | 40000 | 0.2557          | 0.1873 |
+| 0.0388        | 8.8668  | 41000 | 0.2540          | 0.1843 |
+| 0.0317        | 9.0830  | 42000 | 0.2547          | 0.1819 |
+| 0.0334        | 9.2993  | 43000 | 0.2556          | 0.1780 |
+| 0.033         | 9.5156  | 44000 | 0.2552          | 0.1801 |
+| 0.0313        | 9.7318  | 45000 | 0.2540          | 0.1787 |
+| 0.0318        | 9.9481  | 46000 | 0.2537          | 0.1772 |
+| 0.0285        | 10.1644 | 47000 | 0.2534          | 0.1764 |
+| 0.0256        | 10.3806 | 48000 | 0.2530          | 0.1771 |
+| 0.0288        | 10.5969 | 49000 | 0.2532          | 0.1760 |
+| 0.0265        | 10.8131 | 50000 | 0.2530          | 0.1763 |
+
+
+### Framework versions
+
+- Transformers 4.50.0.dev0
+- Pytorch 2.6.0+cu126
+- Datasets 2.16.0
+- Tokenizers 0.21.1

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