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--- |
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base_model: masoudmzb/wav2vec2-xlsr-multilingual-53-fa |
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metrics: |
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- wer |
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widget: |
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- example_title: Common Voice sample 1 |
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src: >- |
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https://huggingface.co/m3hrdadfi/wav2vec2-large-xlsr-persian-v3/resolve/main/sample1.flac |
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- example_title: Common Voice sample 2978 |
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src: >- |
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https://huggingface.co/m3hrdadfi/wav2vec2-large-xlsr-persian-v3/resolve/main/sample2978.flac |
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- example_title: Common Voice sample 5168 |
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src: >- |
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https://huggingface.co/m3hrdadfi/wav2vec2-large-xlsr-persian-v3/resolve/main/sample5168.flac |
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model-index: |
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- name: wav2vec2-large-xlsr-persian-asr-shemo_me7494 |
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results: |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 13.0 fa |
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type: common_voice_13_0 |
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args: fa |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 19.21 |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 13.0 fa |
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type: common_voice_13_0 |
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args: fa |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 19.21 |
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language: |
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- fa |
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pipeline_tag: automatic-speech-recognition |
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tags: |
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- audio |
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- speech |
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- automatic-speech-recognition |
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- asr |
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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_me7494 |
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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) |
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on the [ShEMO](https://github.com/pariajm/sharif-emotional-speech-dataset) dataset. |
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It achieves the following results: |
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- Loss on ShEMO train set: 0.7618 |
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- Loss on ShEMO dev set: 0.6728 |
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- WER on ShEMO train set: 30.47 |
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- WER on ShEMO dev set: 32.85 |
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- WER on Common Voice 13 test set: 19.21 |
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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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| 1.8553 | 0.62 | 100 | 1.4126 | 0.4866 | |
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| 1.4083 | 1.25 | 200 | 1.0428 | 0.4366 | |
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| 1.1718 | 1.88 | 300 | 0.8683 | 0.4127 | |
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| 0.9919 | 2.5 | 400 | 0.7921 | 0.3919 | |
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| 0.9493 | 3.12 | 500 | 0.7676 | 0.3744 | |
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| 0.9414 | 3.75 | 600 | 0.7247 | 0.3695 | |
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| 0.8897 | 4.38 | 700 | 0.7202 | 0.3598 | |
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| 0.8716 | 5.0 | 800 | 0.7096 | 0.3546 | |
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| 0.8467 | 5.62 | 900 | 0.7023 | 0.3499 | |
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| 0.8227 | 6.25 | 1000 | 0.6994 | 0.3411 | |
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| 0.855 | 6.88 | 1100 | 0.6883 | 0.3432 | |
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| 0.8457 | 7.5 | 1200 | 0.6773 | 0.3426 | |
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| 0.7614 | 8.12 | 1300 | 0.6913 | 0.3344 | |
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| 0.8127 | 8.75 | 1400 | 0.6827 | 0.3335 | |
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| 0.8443 | 9.38 | 1500 | 0.6725 | 0.3356 | |
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| 0.7548 | 10.0 | 1600 | 0.6759 | 0.3318 | |
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| 0.7839 | 10.62 | 1700 | 0.6773 | 0.3286 | |
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| 0.7912 | 11.25 | 1800 | 0.6748 | 0.3286 | |
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| 0.8238 | 11.88 | 1900 | 0.6735 | 0.3297 | |
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| 0.7618 | 12.5 | 2000 | 0.6728 | 0.3286 | |
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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 |
