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--- |
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library_name: transformers |
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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-bengali-colab-CV17.0-v2 |
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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: bn |
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split: test |
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args: bn |
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metrics: |
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- name: Wer |
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type: wer |
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value: 1.001531728665208 |
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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-bengali-colab-CV17.0-v2 |
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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: 2.9399 |
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- Wer: 1.0015 |
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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: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 5 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| No log | 0.16 | 50 | 8.6700 | 1.3648 | |
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| 7.4868 | 0.32 | 100 | 6.2568 | 2.1074 | |
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| 7.4868 | 0.48 | 150 | 4.6350 | 1.0779 | |
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| 4.3743 | 0.64 | 200 | 3.6517 | 1.0015 | |
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| 4.3743 | 0.8 | 250 | 3.4099 | 1.0002 | |
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| 3.3984 | 0.96 | 300 | 3.3160 | 1.0004 | |
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| 3.3984 | 1.1184 | 350 | 3.2545 | 1.0004 | |
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| 3.2053 | 1.2784 | 400 | 3.2081 | 1.0004 | |
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| 3.2053 | 1.4384 | 450 | 3.1663 | 1.0007 | |
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| 3.1315 | 1.5984 | 500 | 3.1441 | 1.0004 | |
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| 3.1315 | 1.7584 | 550 | 3.1187 | 1.0004 | |
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| 3.071 | 1.9184 | 600 | 3.1005 | 1.0004 | |
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| 3.071 | 2.0768 | 650 | 3.0800 | 1.0009 | |
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| 3.0241 | 2.2368 | 700 | 3.0587 | 1.0007 | |
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| 3.0241 | 2.3968 | 750 | 3.0362 | 1.0007 | |
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| 2.9979 | 2.5568 | 800 | 3.0259 | 1.0007 | |
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| 2.9979 | 2.7168 | 850 | 3.0151 | 1.0009 | |
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| 2.9738 | 2.8768 | 900 | 3.0034 | 1.0009 | |
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| 2.9738 | 3.0352 | 950 | 2.9906 | 1.0007 | |
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| 2.9602 | 3.1952 | 1000 | 2.9799 | 1.0002 | |
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| 2.9602 | 3.3552 | 1050 | 2.9766 | 1.0007 | |
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| 2.9325 | 3.5152 | 1100 | 2.9698 | 1.0004 | |
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| 2.9325 | 3.6752 | 1150 | 2.9635 | 1.0004 | |
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| 2.8989 | 3.8352 | 1200 | 2.9588 | 1.0009 | |
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| 2.8989 | 3.9952 | 1250 | 2.9507 | 1.0007 | |
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| 2.9026 | 4.1536 | 1300 | 2.9501 | 1.0011 | |
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| 2.9026 | 4.3136 | 1350 | 2.9466 | 1.0007 | |
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| 2.8872 | 4.4736 | 1400 | 2.9435 | 1.0011 | |
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| 2.8872 | 4.6336 | 1450 | 2.9413 | 1.0009 | |
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| 2.9015 | 4.7936 | 1500 | 2.9405 | 1.0011 | |
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| 2.9015 | 4.9536 | 1550 | 2.9399 | 1.0015 | |
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### Framework versions |
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- Transformers 4.56.2 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 3.6.0 |
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- Tokenizers 0.22.1 |
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