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--- |
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base_model: masoudmzb/wav2vec2-xlsr-multilingual-53-fa |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xlsr-persian-asr-shemo_lnxdx |
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results: [] |
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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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# wav2vec2-large-xlsr-persian-asr-shemo_lnxdx |
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This model is a fine-tuned version of [masoudmzb/wav2vec2-xlsr-multilingual-53-fa](https://huggingface.co/masoudmzb/wav2vec2-xlsr-multilingual-53-fa) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7064 |
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- Wer: 0.3344 |
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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: 1e-05 |
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- train_batch_size: 8 |
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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: 16 |
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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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- training_steps: 2000 |
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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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| 1.9455 | 0.62 | 100 | 1.4247 | 0.4831 | |
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| 1.4824 | 1.25 | 200 | 1.1107 | 0.4331 | |
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| 1.2516 | 1.88 | 300 | 0.9141 | 0.4136 | |
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| 1.0859 | 2.5 | 400 | 0.8360 | 0.3975 | |
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| 1.0357 | 3.12 | 500 | 0.8097 | 0.3814 | |
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| 1.0472 | 3.75 | 600 | 0.7550 | 0.3753 | |
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| 0.9963 | 4.38 | 700 | 0.7533 | 0.3636 | |
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| 0.9767 | 5.0 | 800 | 0.7424 | 0.3589 | |
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| 0.9667 | 5.62 | 900 | 0.7360 | 0.3516 | |
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| 0.9385 | 6.25 | 1000 | 0.7355 | 0.3487 | |
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| 0.9805 | 6.88 | 1100 | 0.7237 | 0.3464 | |
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| 0.976 | 7.5 | 1200 | 0.7078 | 0.3455 | |
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| 0.88 | 8.12 | 1300 | 0.7229 | 0.3438 | |
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| 0.9421 | 8.75 | 1400 | 0.7180 | 0.3432 | |
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| 0.9584 | 9.38 | 1500 | 0.7059 | 0.3364 | |
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| 0.88 | 10.0 | 1600 | 0.7106 | 0.3364 | |
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| 0.9113 | 10.62 | 1700 | 0.7125 | 0.3344 | |
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| 0.912 | 11.25 | 1800 | 0.7091 | 0.3353 | |
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| 0.9607 | 11.88 | 1900 | 0.7066 | 0.3344 | |
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| 0.8974 | 12.5 | 2000 | 0.7064 | 0.3344 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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