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update model card README.md
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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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datasets:
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- xtreme_s
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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_300m_mt5-small_minds14.en-US
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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_300m_mt5-small_minds14.en-US
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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 xtreme_s dataset.
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It achieves the following results on the evaluation set:
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- Loss: 4.7321
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- F1: 0.0154
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- Accuracy: 0.0638
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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: 64
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- seed: 42
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- gradient_accumulation_steps: 4
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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: 100
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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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| 2.6067 | 3.95 | 20 | 2.6501 | 0.0112 | 0.0851 |
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| 2.5614 | 7.95 | 40 | 2.8018 | 0.0133 | 0.0603 |
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| 2.2836 | 11.95 | 60 | 3.0786 | 0.0084 | 0.0603 |
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| 1.9597 | 15.95 | 80 | 3.2288 | 0.0126 | 0.0638 |
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| 1.5566 | 19.95 | 100 | 3.6934 | 0.0178 | 0.0567 |
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| 1.3168 | 23.95 | 120 | 3.9135 | 0.0150 | 0.0638 |
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| 1.0598 | 27.95 | 140 | 4.2618 | 0.0084 | 0.0603 |
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| 0.5721 | 31.95 | 160 | 3.7973 | 0.0354 | 0.0780 |
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| 0.4402 | 35.95 | 180 | 4.6233 | 0.0179 | 0.0638 |
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| 0.6113 | 39.95 | 200 | 4.6149 | 0.0208 | 0.0674 |
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| 0.3938 | 43.95 | 220 | 4.7886 | 0.0159 | 0.0638 |
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| 0.2473 | 47.95 | 240 | 4.7321 | 0.0154 | 0.0638 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.11.0+cu113
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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