anah1tbaghdassarian
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w2v-bert-2.0-armenian-colab-CV17.0_10epochs

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 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ---
+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-2.0-armenian-colab-CV17.0_10epochs
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_17_0
+      type: common_voice_17_0
+      config: hy-AM
+      split: test
+      args: hy-AM
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.12119113573407202
 ---
+<!-- 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-armenian-colab-CV17.0_10epochs
+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: 0.1461
+- Wer: 0.1212
+- Cer: 0.0217
+## 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: 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    | Cer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
+| 1.9136        | 1.0   | 325  | 0.2261          | 0.2817 | 0.0493 |
+| 0.1872        | 2.0   | 650  | 0.1762          | 0.2208 | 0.0385 |
+| 0.1168        | 3.0   | 975  | 0.1590          | 0.1807 | 0.0323 |
+| 0.0817        | 4.0   | 1300 | 0.1444          | 0.1614 | 0.0287 |
+| 0.058         | 5.0   | 1625 | 0.1414          | 0.1463 | 0.0259 |
+| 0.0426        | 6.0   | 1950 | 0.1431          | 0.1447 | 0.0257 |
+| 0.0284        | 7.0   | 2275 | 0.1333          | 0.1390 | 0.0251 |
+| 0.0185        | 8.0   | 2600 | 0.1353          | 0.1254 | 0.0225 |
+| 0.0114        | 9.0   | 2925 | 0.1434          | 0.1233 | 0.0219 |
+| 0.007         | 10.0  | 3250 | 0.1461          | 0.1212 | 0.0217 |
+### Framework versions
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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