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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_17_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: results
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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_17_0
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+ type: common_voice_17_0
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+ config: ne-NP
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+ split: validated+other
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+ args: ne-NP
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.5865921787709497
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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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+ # results
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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_17_0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7289
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+ - Wer: 0.5866
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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: 200
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+ - num_epochs: 30
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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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+ | 1.4919 | 2.9851 | 100 | 1.2236 | 0.9106 |
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+ | 1.0086 | 5.9701 | 200 | 0.9436 | 0.8291 |
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+ | 0.6072 | 8.9552 | 300 | 0.8277 | 0.7117 |
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+ | 0.55 | 11.9403 | 400 | 0.7774 | 0.6726 |
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+ | 0.3398 | 14.9254 | 500 | 0.7344 | 0.6212 |
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+ | 0.2543 | 17.9104 | 600 | 0.7368 | 0.6212 |
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+ | 0.3558 | 20.8955 | 700 | 0.7313 | 0.5788 |
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+ | 0.1751 | 23.8806 | 800 | 0.7060 | 0.5855 |
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+ | 0.1502 | 26.8657 | 900 | 0.7289 | 0.5866 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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