End of training
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README.md
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---
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base_model: ylacombe/w2v-bert-2.0
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_16_0
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metrics:
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- wer
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model-index:
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- name: w2v-bert-2.0-600m-turkish-colab
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: common_voice_16_0
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type: common_voice_16_0
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config: tr
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split: test
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args: tr
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metrics:
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- name: Wer
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type: wer
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value: 0.13727393664832993
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# w2v-bert-2.0-600m-turkish-colab
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This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the common_voice_16_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1441
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- Wer: 0.1373
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 5
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 0.252 | 0.29 | 400 | 0.3121 | 0.3150 |
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| 0.2541 | 0.58 | 800 | 0.3786 | 0.3441 |
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| 0.2505 | 0.88 | 1200 | 0.4106 | 0.3766 |
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| 0.1958 | 1.17 | 1600 | 0.2974 | 0.2877 |
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| 0.1686 | 1.46 | 2000 | 0.2854 | 0.2736 |
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| 0.1498 | 1.75 | 2400 | 0.2508 | 0.2486 |
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| 0.1343 | 2.05 | 2800 | 0.2315 | 0.2263 |
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| 0.1045 | 2.34 | 3200 | 0.2207 | 0.2243 |
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| 0.0983 | 2.63 | 3600 | 0.2109 | 0.2046 |
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| 0.089 | 2.92 | 4000 | 0.1970 | 0.1896 |
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| 0.0726 | 3.21 | 4400 | 0.1963 | 0.1799 |
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| 0.0552 | 3.51 | 4800 | 0.1879 | 0.1778 |
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| 0.0573 | 3.8 | 5200 | 0.1821 | 0.1693 |
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| 0.0421 | 4.09 | 5600 | 0.1602 | 0.1517 |
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| 0.0363 | 4.38 | 6000 | 0.1564 | 0.1485 |
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| 0.0345 | 4.67 | 6400 | 0.1466 | 0.1437 |
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| 0.0294 | 4.97 | 6800 | 0.1441 | 0.1373 |
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### Framework versions
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- Transformers 4.37.0.dev0
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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model.safetensors
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runs/Jan09_13-05-45_ed9085e82d2d/events.out.tfevents.1704806071.ed9085e82d2d.32553.0
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