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wav2vec2-bert-swahili-noise

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 ---
 library_name: transformers
-tags: []
 ---
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 ---
 library_name: transformers
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+datasets:
+- generator
+metrics:
+- wer
+model-index:
+- name: wav2vec2-bert-swahili-noise
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: generator
+      type: generator
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.2959163543105149
 ---
+<!-- 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-bert-swahili-noise
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the generator dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5771
+- Wer: 0.2959
+## 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: 38
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_BNB 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: 100
+- training_steps: 900
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 3.142         | 0.0817 | 100  | 3.0798          | 0.9999 |
+| 1.9368        | 0.1634 | 200  | 1.4137          | 0.9886 |
+| 0.9455        | 0.2451 | 300  | 0.7745          | 0.4115 |
+| 0.8236        | 0.3268 | 400  | 0.6644          | 0.3485 |
+| 0.7723        | 0.4085 | 500  | 0.6475          | 0.3313 |
+| 0.7603        | 0.4902 | 600  | 0.6082          | 0.3097 |
+| 0.6848        | 0.5719 | 700  | 0.5972          | 0.3072 |
+| 0.683         | 0.6536 | 800  | 0.5762          | 0.2986 |
+| 0.6967        | 0.7353 | 900  | 0.5771          | 0.2959 |
+### Framework versions
+- Transformers 4.50.3
+- Pytorch 2.8.0+cu128
+- Datasets 3.6.0
+- Tokenizers 0.21.2