davidilag
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wav2vec2-xls-r-1b-irish-5h-11k-steps

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 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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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-irish-5h-11k-steps
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_17_0
+      type: common_voice_17_0
+      config: ga-IE
+      split: test
+      args: ga-IE
+    metrics:
+    - name: Wer
+      type: wer
+      value: 99.97108991037872
 ---
+<!-- 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-irish-5h-11k-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: nan
+- Wer: 99.9711
+- Cer: 99.9943
+## 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     |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
+| 2.9708        | 6.25  | 1000  | 2.8622          | 94.9986 | 93.1290 |
+| 4.3506        | 12.5  | 2000  | 4.2474          | 96.5019 | 92.1035 |
+| 4.4125        | 18.75 | 3000  | 4.2473          | 96.5019 | 92.2060 |
+| 4.4092        | 25.0  | 4000  | 4.2474          | 96.3862 | 91.9781 |
+| 4.436         | 31.25 | 5000  | 4.2474          | 96.4151 | 92.0978 |
+| 4.4694        | 37.5  | 6000  | 4.2473          | 96.4441 | 92.1206 |
+| 4.3806        | 43.75 | 7000  | 4.2474          | 96.3862 | 92.1775 |
+| 4.4963        | 50.0  | 8000  | 4.2473          | 96.3862 | 92.0579 |
+| 0.0           | 56.25 | 9000  | nan             | 99.9711 | 99.9943 |
+| 0.0           | 62.5  | 10000 | nan             | 99.9711 | 99.9943 |
+| 0.0           | 68.75 | 11000 | nan             | 99.9711 | 99.9943 |
+### Framework versions
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

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