End of training

README.md

@@ -1,3 +1,126 @@
----
-license: mit
----
+---
+library_name: transformers
+language:
+- vi
+license: apache-2.0
+base_model: openai/whisper-base
+tags:
+- generated_from_trainer
+datasets:
+- doof-ferb/vlsp2020_vinai_100h
+metrics:
+- wer
+model-index:
+- name: Whisper base Vi - Nam Phung
+  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 base Vi - Nam Phung
+
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the vlsp2020_vinai_100h dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3606
+- Wer: 16.9148
+
+## 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: 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_steps: 500
+- training_steps: 15000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
+|:-------------:|:------:|:-----:|:---------------:|:-------:|
+| 0.7975        | 0.0886 | 250   | 0.7610          | 36.8155 |
+| 0.6074        | 0.1772 | 500   | 0.6467          | 32.4870 |
+| 0.5934        | 0.2658 | 750   | 0.5843          | 29.5521 |
+| 0.5497        | 0.3544 | 1000  | 0.5450          | 26.5531 |
+| 0.5559        | 0.4429 | 1250  | 0.5176          | 26.0146 |
+| 0.4872        | 0.5315 | 1500  | 0.4967          | 25.8677 |
+| 0.5001        | 0.6201 | 1750  | 0.4795          | 25.0705 |
+| 0.4597        | 0.7087 | 2000  | 0.4644          | 24.5844 |
+| 0.4507        | 0.7973 | 2250  | 0.4536          | 22.6308 |
+| 0.4356        | 0.8859 | 2500  | 0.4412          | 22.1019 |
+| 0.4589        | 0.9745 | 2750  | 0.4315          | 22.3294 |
+| 0.3347        | 1.0631 | 3000  | 0.4250          | 21.2764 |
+| 0.3318        | 1.1517 | 3250  | 0.4204          | 20.9716 |
+| 0.3473        | 1.2403 | 3500  | 0.4134          | 20.9027 |
+| 0.3358        | 1.3288 | 3750  | 0.4097          | 20.2717 |
+| 0.3467        | 1.4174 | 4000  | 0.4034          | 20.3648 |
+| 0.3325        | 1.5060 | 4250  | 0.3987          | 19.7828 |
+| 0.3396        | 1.5946 | 4500  | 0.3938          | 20.0876 |
+| 0.3429        | 1.6832 | 4750  | 0.3897          | 18.9360 |
+| 0.3347        | 1.7718 | 5000  | 0.3852          | 19.5118 |
+| 0.3318        | 1.8604 | 5250  | 0.3816          | 19.1070 |
+| 0.3362        | 1.9490 | 5500  | 0.3765          | 19.3152 |
+| 0.3083        | 2.0376 | 5750  | 0.3780          | 18.7174 |
+| 0.2372        | 2.1262 | 6000  | 0.3779          | 18.7188 |
+| 0.2534        | 2.2147 | 6250  | 0.3742          | 18.6181 |
+| 0.271         | 2.3033 | 6500  | 0.3729          | 18.5588 |
+| 0.2836        | 2.3919 | 6750  | 0.3718          | 18.3712 |
+| 0.2648        | 2.4805 | 7000  | 0.3689          | 18.3843 |
+| 0.2678        | 2.5691 | 7250  | 0.3665          | 17.6009 |
+| 0.2714        | 2.6577 | 7500  | 0.3652          | 17.7202 |
+| 0.2504        | 2.7463 | 7750  | 0.3640          | 17.9457 |
+| 0.275         | 2.8349 | 8000  | 0.3631          | 17.7382 |
+| 0.2538        | 2.9235 | 8250  | 0.3598          | 17.3451 |
+| 0.1795        | 3.0120 | 8500  | 0.3612          | 17.2499 |
+| 0.1879        | 3.1006 | 8750  | 0.3648          | 17.5003 |
+| 0.1947        | 3.1892 | 9000  | 0.3627          | 17.2665 |
+| 0.1968        | 3.2778 | 9250  | 0.3620          | 17.0700 |
+| 0.1954        | 3.3664 | 9500  | 0.3621          | 17.1148 |
+| 0.1921        | 3.4550 | 9750  | 0.3617          | 17.0251 |
+| 0.2068        | 3.5436 | 10000 | 0.3601          | 17.2162 |
+| 0.2115        | 3.6322 | 10250 | 0.3604          | 17.0293 |
+| 0.2242        | 3.7208 | 10500 | 0.3591          | 16.8072 |
+| 0.2015        | 3.8094 | 10750 | 0.3574          | 17.0858 |
+| 0.2261        | 3.8979 | 11000 | 0.3573          | 16.7017 |
+| 0.2129        | 3.9865 | 11250 | 0.3556          | 17.1631 |
+| 0.1739        | 4.0751 | 11500 | 0.3603          | 16.8362 |
+| 0.1532        | 4.1637 | 11750 | 0.3603          | 16.8603 |
+| 0.1408        | 4.2523 | 12000 | 0.3613          | 16.8631 |
+| 0.1743        | 4.3409 | 12250 | 0.3604          | 16.8196 |
+| 0.1832        | 4.4295 | 12500 | 0.3613          | 16.9534 |
+| 0.1688        | 4.5181 | 12750 | 0.3609          | 17.0279 |
+| 0.1767        | 4.6067 | 13000 | 0.3595          | 17.1865 |
+| 0.1589        | 4.6953 | 13250 | 0.3596          | 16.8824 |
+| 0.1778        | 4.7838 | 13500 | 0.3591          | 16.8376 |
+| 0.1806        | 4.8724 | 13750 | 0.3590          | 16.8714 |
+| 0.1551        | 4.9610 | 14000 | 0.3591          | 16.8231 |
+| 0.163         | 5.0496 | 14250 | 0.3598          | 16.9541 |
+| 0.1365        | 5.1382 | 14500 | 0.3604          | 16.8079 |
+| 0.1563        | 5.2268 | 14750 | 0.3606          | 16.9176 |
+| 0.1429        | 5.3154 | 15000 | 0.3606          | 16.9148 |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1

generation_config.json

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+}

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