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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- f1
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- accuracy
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model-index:
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- name: xtreme_s_xlsr_minds14_rerun
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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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# xtreme_s_xlsr_minds14_rerun
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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 None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2890
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- F1: 0.9474
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- Accuracy: 0.9470
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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: 32
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- total_train_batch_size: 64
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- total_eval_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: 1500
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- num_epochs: 50.0
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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 | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
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| 2.551 | 2.7 | 200 | 2.5855 | 0.0407 | 0.1201 |
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| 1.6934 | 5.41 | 400 | 1.5072 | 0.5862 | 0.6085 |
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| 0.5914 | 8.11 | 600 | 0.7274 | 0.8270 | 0.8232 |
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| 0.3896 | 10.81 | 800 | 0.4402 | 0.8905 | 0.8890 |
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| 0.5052 | 13.51 | 1000 | 0.4483 | 0.8837 | 0.8829 |
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| 0.4806 | 16.22 | 1200 | 0.4981 | 0.8784 | 0.8787 |
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| 0.2103 | 18.92 | 1400 | 0.4957 | 0.8810 | 0.8817 |
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| 0.4198 | 21.62 | 1600 | 0.5161 | 0.8927 | 0.8921 |
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| 0.11 | 24.32 | 1800 | 0.4456 | 0.8923 | 0.8902 |
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| 0.1233 | 27.03 | 2000 | 0.3858 | 0.9016 | 0.9012 |
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| 0.1827 | 29.73 | 2200 | 0.3765 | 0.9162 | 0.9159 |
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| 0.1235 | 32.43 | 2400 | 0.3716 | 0.9134 | 0.9128 |
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| 0.1873 | 35.14 | 2600 | 0.3080 | 0.9314 | 0.9311 |
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| 0.017 | 37.84 | 2800 | 0.2629 | 0.9415 | 0.9409 |
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| 0.0436 | 40.54 | 3000 | 0.3159 | 0.9397 | 0.9390 |
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| 0.0455 | 43.24 | 3200 | 0.2963 | 0.9393 | 0.9390 |
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| 0.046 | 45.95 | 3400 | 0.2914 | 0.9457 | 0.9451 |
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| 0.0042 | 48.65 | 3600 | 0.2890 | 0.9474 | 0.9470 |
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### Framework versions
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- Transformers 4.18.0.dev0
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- Pytorch 1.10.2+cu113
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- Datasets 1.18.4.dev0
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- Tokenizers 0.11.6
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