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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_partial |
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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_partial |
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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: 0.8069 |
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- Wer: 0.3490 |
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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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| 2.3226 | 0.62 | 100 | 1.4548 | 0.4851 | |
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| 1.7166 | 1.25 | 200 | 1.2460 | 0.4279 | |
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| 1.4987 | 1.88 | 300 | 1.0671 | 0.4194 | |
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| 1.3771 | 2.5 | 400 | 0.9784 | 0.4054 | |
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| 1.3217 | 3.12 | 500 | 0.9450 | 0.3905 | |
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| 1.3272 | 3.75 | 600 | 0.8851 | 0.3841 | |
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| 1.3025 | 4.38 | 700 | 0.8748 | 0.3779 | |
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| 1.2719 | 5.0 | 800 | 0.8674 | 0.3724 | |
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| 1.2563 | 5.62 | 900 | 0.8467 | 0.3692 | |
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| 1.2451 | 6.25 | 1000 | 0.8440 | 0.3645 | |
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| 1.2585 | 6.88 | 1100 | 0.8292 | 0.3610 | |
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| 1.2633 | 7.5 | 1200 | 0.8137 | 0.3601 | |
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| 1.1923 | 8.12 | 1300 | 0.8263 | 0.3575 | |
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| 1.2349 | 8.75 | 1400 | 0.8184 | 0.3551 | |
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| 1.2511 | 9.38 | 1500 | 0.8078 | 0.3516 | |
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| 1.1779 | 10.0 | 1600 | 0.8102 | 0.3505 | |
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| 1.2161 | 10.62 | 1700 | 0.8123 | 0.3499 | |
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| 1.1967 | 11.25 | 1800 | 0.8086 | 0.3502 | |
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| 1.2454 | 11.88 | 1900 | 0.8066 | 0.3490 | |
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| 1.1928 | 12.5 | 2000 | 0.8069 | 0.3490 | |
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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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