davidilag
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wav2vec2-xls-r-1b-faroese-100h-10k-steps

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 ---
 library_name: transformers
-tags: []
 ---
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 ---
 library_name: transformers
+license: apache-2.0
+base_model: facebook/wav2vec2-xls-r-1b
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: wav2vec2-xls-r-1b-faroese-100h-10k-steps
+  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-1b-faroese-100h-10k-steps
+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.
+It achieves the following results on the evaluation set:
+- Loss: 2.4747
+- Wer: 100.0
+- Cer: 82.7552
+## 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: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- 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: 10000
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch  | Step  | Validation Loss | Wer     | Cer     |
+|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|
+| 2.0903        | 0.4640 | 1000  | 0.6799          | 73.2837 | 24.4656 |
+| 2.872         | 0.9281 | 2000  | 0.9368          | 81.5331 | 31.3250 |
+| 2.9863        | 1.3921 | 3000  | 0.8913          | 79.8873 | 29.0572 |
+| 2.5887        | 1.8561 | 4000  | 0.9178          | 81.5633 | 30.7605 |
+| 2.5408        | 2.3202 | 5000  | 1.0047          | 85.0765 | 35.1896 |
+| 3.057         | 2.7842 | 6000  | 1.0349          | 82.6958 | 32.6409 |
+| 6.9153        | 3.2483 | 7000  | 2.9900          | 100.0   | 98.8214 |
+| 24.2761       | 3.7123 | 8000  | 11.5877         | 100.0   | 98.8530 |
+| 5.0923        | 4.1763 | 9000  | 2.3517          | 100.0   | 90.6749 |
+| 5.2345        | 4.6404 | 10000 | 2.4747          | 100.0   | 82.7552 |
+### Framework versions
+- Transformers 4.46.1
+- Pytorch 2.5.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.2

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