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wav2vec2-base-fleurs-329-colab-a100-2

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 ---
+license: apache-2.0
+base_model: facebook/wav2vec2-base-960h
+tags:
+- generated_from_trainer
+datasets:
+- fleurs
+metrics:
+- wer
+model-index:
+- name: wav2vec2-base-fleurs-329-colab-a100-2
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: fleurs
+      type: fleurs
+      config: en_us
+      split: test
+      args: en_us
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.9917617237008872
 ---
+<!-- 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-base-fleurs-329-colab-a100-2
+This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the fleurs dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.5431
+- Wer: 0.9918
+## 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: 1e-05
+- 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
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 8.5696        | 2.45  | 200  | 5.0490          | 1.0    |
+| 4.0587        | 4.91  | 400  | 3.3808          | 1.0    |
+| 3.0272        | 7.36  | 600  | 2.7368          | 0.9954 |
+| 2.6659        | 9.82  | 800  | 2.5431          | 0.9918 |
+### Framework versions
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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