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--- |
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license: mit |
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base_model: facebook/w2v-bert-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-2.0-armenian-colab-CV17.0_10epochs |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_17_0 |
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type: common_voice_17_0 |
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config: hy-AM |
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split: test |
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args: hy-AM |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.12119113573407202 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# w2v-bert-2.0-armenian-colab-CV17.0_10epochs |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1461 |
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- Wer: 0.1212 |
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- Cer: 0.0217 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 1.9136 | 1.0 | 325 | 0.2261 | 0.2817 | 0.0493 | |
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| 0.1872 | 2.0 | 650 | 0.1762 | 0.2208 | 0.0385 | |
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| 0.1168 | 3.0 | 975 | 0.1590 | 0.1807 | 0.0323 | |
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| 0.0817 | 4.0 | 1300 | 0.1444 | 0.1614 | 0.0287 | |
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| 0.058 | 5.0 | 1625 | 0.1414 | 0.1463 | 0.0259 | |
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| 0.0426 | 6.0 | 1950 | 0.1431 | 0.1447 | 0.0257 | |
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| 0.0284 | 7.0 | 2275 | 0.1333 | 0.1390 | 0.0251 | |
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| 0.0185 | 8.0 | 2600 | 0.1353 | 0.1254 | 0.0225 | |
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| 0.0114 | 9.0 | 2925 | 0.1434 | 0.1233 | 0.0219 | |
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| 0.007 | 10.0 | 3250 | 0.1461 | 0.1212 | 0.0217 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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