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End of training

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README.md ADDED
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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-fine-tune-test-no-punct4
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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: 0.436
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+ ---
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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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+
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+ # w2v-fine-tune-test-no-punct4
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+
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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: 0.7511
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+ - Wer: 0.436
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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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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+ - 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: 20
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+ - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----:|
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+ | 4.367 | 1.54 | 20 | 3.3453 | 1.0 |
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+ | 2.1265 | 3.08 | 40 | 1.7730 | 0.996 |
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+ | 0.4755 | 4.62 | 60 | 0.8654 | 0.684 |
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+ | 0.203 | 6.15 | 80 | 0.7436 | 0.56 |
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+ | 0.1251 | 7.69 | 100 | 0.8143 | 0.548 |
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+ | 0.0449 | 9.23 | 120 | 0.7511 | 0.436 |
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+
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+
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+ ### Framework versions
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+
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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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