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- model.safetensors +1 -1
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: facebook/wav2vec2-xls-r-1b
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: xls-r-1b-bem-natbed-non-native-model
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results: []
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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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# xls-r-1b-bem-natbed-non-native-model
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6899
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- Wer: 0.6880
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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: 0.0003
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- train_batch_size: 8
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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: 16
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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: 100
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- num_epochs: 30.0
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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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| 3.8975 | 0.4515 | 100 | 1.1343 | 0.9316 |
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| 1.0247 | 0.9029 | 200 | 0.9811 | 0.8826 |
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| 0.9631 | 1.3544 | 300 | 0.8108 | 0.7524 |
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| 0.8711 | 1.8059 | 400 | 0.7749 | 0.7638 |
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| 0.7935 | 2.2573 | 500 | 0.8008 | 0.8232 |
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| 0.7869 | 2.7088 | 600 | 0.7334 | 0.7262 |
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| 0.7265 | 3.1603 | 700 | 0.7239 | 0.6950 |
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| 0.7011 | 3.6117 | 800 | 0.7077 | 0.6807 |
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| 0.7343 | 4.0632 | 900 | 0.6985 | 0.6914 |
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| 0.6624 | 4.5147 | 1000 | 0.6818 | 0.7142 |
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| 0.6642 | 4.9661 | 1100 | 0.7097 | 0.6968 |
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| 0.6064 | 5.4176 | 1200 | 0.7195 | 0.6856 |
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| 0.5867 | 5.8691 | 1300 | 0.6899 | 0.6880 |
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### Framework versions
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- Transformers 4.46.0.dev0
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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model.safetensors
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