EzraWilliam
/

wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod16

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 ---
-library_name: transformers
-tags: []
 ---
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 ---
+license: apache-2.0
+base_model: facebook/wav2vec2-xls-r-300m
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_13_0
+metrics:
+- wer
+model-index:
+- name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod16
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_13_0
+      type: common_voice_13_0
+      config: id
+      split: test
+      args: id
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.31356010324483774
 ---
+<!-- 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-xlsr-53-CV-demo-google-colab-Ezra_William_Prod16
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_13_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3425
+- Wer: 0.3136
+## 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
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 12
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 2.9562        | 1.0   | 278  | 2.9246          | 1.0    |
+| 2.8689        | 2.0   | 556  | 2.7856          | 1.0    |
+| 1.1264        | 3.0   | 834  | 0.6656          | 0.6370 |
+| 0.6913        | 4.0   | 1112 | 0.5009          | 0.5000 |
+| 0.5835        | 5.0   | 1390 | 0.4370          | 0.4477 |
+| 0.4684        | 6.0   | 1668 | 0.3923          | 0.3857 |
+| 0.4139        | 7.0   | 1946 | 0.3876          | 0.3761 |
+| 0.389         | 8.0   | 2224 | 0.3881          | 0.3551 |
+| 0.3559        | 9.0   | 2502 | 0.3580          | 0.3387 |
+| 0.3228        | 10.0  | 2780 | 0.3552          | 0.3249 |
+| 0.3295        | 11.0  | 3058 | 0.3385          | 0.3197 |
+| 0.3112        | 12.0  | 3336 | 0.3425          | 0.3136 |
+### Framework versions
+- Transformers 4.40.0
+- Pytorch 2.2.2+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

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