UmarRamzan
commited on
End of training
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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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base_model: facebook/w2v-bert-2.0
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datasets:
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- common_voice_17_0
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metrics:
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- name: w2v2-bert-urdu
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results:
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- task:
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type: automatic-speech-recognition
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name: 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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split: test[:100]
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args: ur
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metrics:
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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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# w2v2-bert-urdu
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This model
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It achieves the following results on the evaluation set:
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- Loss:
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- Wer: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-
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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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- 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:
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- num_epochs: 2
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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### Framework versions
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---
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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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- name: w2v2-bert-urdu
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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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split: test[:100]
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args: ur
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metrics:
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- name: Wer
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type: wer
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value: 0.3300546448087432
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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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# w2v2-bert-urdu
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This model was trained from scratch 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: 0.4246
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- Wer: 0.3301
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-06
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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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- 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: 100
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- num_epochs: 2
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:------:|:----:|:---------------:|:------:|
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| 0.8145 | 0.1695 | 50 | 0.4620 | 0.3421 |
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| 0.4364 | 0.3390 | 100 | 0.3969 | 0.2874 |
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| 0.418 | 0.5085 | 150 | 0.3697 | 0.2820 |
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| 0.402 | 0.6780 | 200 | 0.3627 | 0.2842 |
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| 0.3698 | 0.8475 | 250 | 0.3314 | 0.2710 |
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| 0.3779 | 1.0169 | 300 | 0.3292 | 0.2852 |
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| 0.3167 | 1.1864 | 350 | 0.3230 | 0.2820 |
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| 0.3578 | 1.3559 | 400 | 0.3825 | 0.2940 |
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| 0.4189 | 1.5254 | 450 | 0.4225 | 0.3104 |
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| 0.4803 | 1.6949 | 500 | 0.4248 | 0.3311 |
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| 0.4612 | 1.8644 | 550 | 0.4246 | 0.3301 |
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### Framework versions
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model.safetensors
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runs/May12_18-22-06_1d4a7576e075/events.out.tfevents.1715538284.1d4a7576e075.1900.1
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