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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-xls-r-300m
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-large-xls-r-300m-tr-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
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+ type: common_voice
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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: 0.3005821672964968
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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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+ # wav2vec2-large-xls-r-300m-tr-colab
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3889
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+ - Wer: 0.3006
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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: 0.0003
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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: 500
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+ - num_epochs: 30
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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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+ | 3.8274 | 3.67 | 400 | 0.6752 | 0.6946 |
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+ | 0.4002 | 7.34 | 800 | 0.4440 | 0.5183 |
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+ | 0.1961 | 11.01 | 1200 | 0.4133 | 0.4052 |
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+ | 0.1285 | 14.68 | 1600 | 0.4249 | 0.3737 |
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+ | 0.0966 | 18.35 | 2000 | 0.4019 | 0.3606 |
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+ | 0.0789 | 22.02 | 2400 | 0.4019 | 0.3316 |
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+ | 0.0599 | 25.69 | 2800 | 0.3996 | 0.3078 |
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+ | 0.047 | 29.36 | 3200 | 0.3889 | 0.3006 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.3
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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