TJLeiber
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wav2vec2-standard_model0-xlsr-53-fr-colab

@@ -1,199 +1,83 @@
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 ---
+language:
+- fr
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53
+tags:
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_17_0
+metrics:
+- wer
+model-index:
+- name: acoustic_model0_cv_17_fr_XLSR-53
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 17
+      type: mozilla-foundation/common_voice_17_0
+      config: fr
+      split: test
+      args: fr
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.533356948872358
 ---
+<!-- 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. -->
+# acoustic_model0_cv_17_fr_XLSR-53
+This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the Common Voice 17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5859
+- Wer: 0.5334
+## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 1200
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 7.2           | 2.105  | 400  | 3.0327          | 0.9949 |
+| 2.8531        | 5.0958 | 800  | 1.5473          | 0.9133 |
+| 1.0966        | 8.0867 | 1200 | 0.5859          | 0.5334 |
+### Framework versions
+- Transformers 4.40.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1