sulaimank
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w2v-bert-cv-grain-lg_cv_only

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 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ---
 library_name: transformers
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_17_0
+metrics:
+- wer
+model-index:
+- name: w2v-bert-cv-grain-lg_cv_only
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_17_0
+      type: common_voice_17_0
+      config: lg
+      split: test[:10%]
+      args: lg
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.5799642969652421
 ---
+<!-- 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. -->
+# w2v-bert-cv-grain-lg_cv_only
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_17_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: inf
+- Wer: 0.5800
+- Cer: 0.1379
+## 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: 5e-05
+- 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
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
+| 0.5013        | 1.0   | 2221  | inf             | 0.2789 | 0.0724 |
+| 0.299         | 2.0   | 4442  | inf             | 0.2501 | 0.0648 |
+| 0.2554        | 3.0   | 6663  | inf             | 0.2435 | 0.0685 |
+| 0.2411        | 4.0   | 8884  | inf             | 0.2447 | 0.0648 |
+| 0.2886        | 5.0   | 11105 | inf             | 0.2506 | 0.0654 |
+| 0.3923        | 6.0   | 13326 | inf             | 0.4237 | 0.1108 |
+| 2.1779        | 7.0   | 15547 | inf             | 0.5612 | 0.1439 |
+| 4.5629        | 8.0   | 17768 | inf             | 0.5152 | 0.1379 |
+| 2.236         | 9.0   | 19989 | inf             | 0.5787 | 0.1384 |
+| 2.2033        | 10.0  | 22210 | inf             | 0.5742 | 0.1375 |
+| 2.2047        | 11.0  | 24431 | inf             | 0.5784 | 0.1382 |
+| 2.2057        | 12.0  | 26652 | inf             | 0.5805 | 0.1390 |
+| 2.2076        | 13.0  | 28873 | inf             | 0.5800 | 0.1379 |
+### Framework versions
+- Transformers 4.46.1
+- Pytorch 2.1.0+cu118
+- Datasets 3.1.0
+- Tokenizers 0.20.1

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