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wav2vec2-xls-r-300m-closest-to-faroese-full-15k-steps_v7

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 ---
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 ---
 library_name: transformers
+license: apache-2.0
+base_model: facebook/wav2vec2-xls-r-300m
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: wav2vec2-xls-r-300m-closest-to-faroese-full-15k-steps_v7
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# wav2vec2-xls-r-300m-closest-to-faroese-full-15k-steps_v7
+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.
+It achieves the following results on the evaluation set:
+- Loss: 1.2472
+- Wer: 95.4633
+- Cer: 32.3403
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 0.0003
+- train_batch_size: 2
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 15000
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch  | Step  | Validation Loss | Wer     | Cer     |
+|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|
+| 13.1629       | 0.3349 | 1000  | 0.6152          | 63.3285 | 18.8424 |
+| 10.2766       | 0.6698 | 2000  | 0.4313          | 49.4623 | 13.6814 |
+| 7.9374        | 1.0044 | 3000  | 0.3649          | 43.9210 | 11.8791 |
+| 7.6787        | 1.3392 | 4000  | 0.3353          | 40.3217 | 10.5091 |
+| 7.4414        | 1.6741 | 5000  | 0.3097          | 38.5529 | 10.0199 |
+| 5.6641        | 2.0087 | 6000  | 0.2806          | 37.1760 | 9.5132  |
+| 19.8102       | 2.3436 | 7000  | 1.0119          | 81.0784 | 25.2870 |
+| 21.6448       | 2.6785 | 8000  | 1.1365          | 77.7051 | 26.4944 |
+| 20.3363       | 3.0131 | 9000  | 1.0859          | 88.1525 | 32.7446 |
+| 20.0312       | 3.3479 | 10000 | 1.0513          | 88.4973 | 30.9106 |
+| 21.5903       | 3.6828 | 11000 | 1.0996          | 90.2825 | 32.8604 |
+| 21.0909       | 4.0174 | 12000 | 1.0407          | 84.0173 | 26.3710 |
+| 23.4511       | 4.3523 | 13000 | 1.2414          | 80.7754 | 24.7467 |
+| 23.5201       | 4.6872 | 14000 | 1.2473          | 95.4625 | 32.3366 |
+| 24.6061       | 5.0218 | 15000 | 1.2472          | 95.4633 | 32.3403 |
+### Framework versions
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0