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w2v-bert-2.0-mongolian-colab-CV16.0

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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_16_0
+metrics:
+- wer
+model-index:
+- name: w2v-bert-2.0-mongolian-colab-CV16.0
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_16_0
+      type: common_voice_16_0
+      config: mn
+      split: test
+      args: mn
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.3261909941266043
 ---
+<!-- 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-2.0-mongolian-colab-CV16.0
+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_16_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5208
+- Wer: 0.3262
+## 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
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 0.4267        | 2.3794 | 300  | 0.6658          | 0.5124 |
+| 0.3386        | 4.7510 | 600  | 0.5587          | 0.4490 |
+| 0.1766        | 7.1225 | 900  | 0.5474          | 0.3609 |
+| 0.0746        | 9.4941 | 1200 | 0.5208          | 0.3262 |
+### Framework versions
+- Transformers 4.46.2
+- Pytorch 2.4.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.20.0

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