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wav2vec2-xls-r-1b-danish-12h-6k-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
+datasets:
+- common_voice_17_0
+metrics:
+- wer
+model-index:
+- name: wav2vec2-xls-r-1b-danish-12h-6k-steps
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_17_0
+      type: common_voice_17_0
+      config: da
+      split: test
+      args: da
+    metrics:
+    - name: Wer
+      type: wer
+      value: 29.80512727765972
 ---
+<!-- 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-danish-12h-6k-steps
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_17_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4179
+- Wer: 29.8051
+- Cer: 9.5826
+## 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: 0.0001
+- 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: 3000
+- training_steps: 11000
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch   | Step  | Validation Loss | Wer     | Cer     |
+|:-------------:|:-------:|:-----:|:---------------:|:-------:|:-------:|
+| 0.9182        | 5.3333  | 1000  | 0.5134          | 53.0768 | 16.3044 |
+| 0.2894        | 10.6667 | 2000  | 0.3309          | 35.3529 | 10.9777 |
+| 0.2917        | 16.0    | 3000  | 0.3877          | 38.0657 | 12.0348 |
+| 0.1964        | 21.3333 | 4000  | 0.4244          | 36.1713 | 11.4545 |
+| 0.1227        | 26.6667 | 5000  | 0.4213          | 36.4335 | 11.6030 |
+| 0.1455        | 32.0    | 6000  | 0.4112          | 34.1412 | 10.9986 |
+| 0.1005        | 37.3333 | 7000  | 0.4383          | 33.8563 | 10.8228 |
+| 0.0604        | 42.6667 | 8000  | 0.4381          | 33.0379 | 10.5787 |
+| 0.0616        | 48.0    | 9000  | 0.4445          | 31.4826 | 10.0955 |
+| 0.0425        | 53.3333 | 10000 | 0.4412          | 30.7637 | 9.8170  |
+| 0.0326        | 58.6667 | 11000 | 0.4179          | 29.8051 | 9.5826  |
+### Framework versions
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3