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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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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: wav2vec2-Malayalam |
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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: ml |
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split: None |
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args: ml |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.908768536428111 |
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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-Malayalam |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) 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: 0.7479 |
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- Wer: 0.9088 |
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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: 0.0003 |
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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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- gradient_accumulation_steps: 2 |
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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: 500 |
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- num_epochs: 30 |
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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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| 8.6036 | 1.5748 | 100 | 6.5081 | 1.0 | |
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| 3.5056 | 3.1496 | 200 | 3.5634 | 1.0 | |
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| 3.4952 | 4.7244 | 300 | 3.4927 | 1.0 | |
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| 3.3772 | 6.2992 | 400 | 3.3696 | 1.0 | |
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| 3.1849 | 7.8740 | 500 | 3.1735 | 1.0 | |
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| 1.3056 | 9.4488 | 600 | 1.2938 | 1.1167 | |
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| 0.8162 | 11.0236 | 700 | 0.8301 | 1.0190 | |
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| 0.6022 | 12.5984 | 800 | 0.7678 | 0.9929 | |
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| 0.454 | 14.1732 | 900 | 0.7514 | 0.9832 | |
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| 0.4104 | 15.7480 | 1000 | 0.7168 | 0.9452 | |
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| 0.3616 | 17.3228 | 1100 | 0.7297 | 0.9571 | |
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| 0.2951 | 18.8976 | 1200 | 0.6925 | 0.9555 | |
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| 0.2667 | 20.4724 | 1300 | 0.7254 | 0.9400 | |
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| 0.2707 | 22.0472 | 1400 | 0.7498 | 0.9101 | |
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| 0.2263 | 23.6220 | 1500 | 0.7093 | 0.9120 | |
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| 0.1933 | 25.1969 | 1600 | 0.7396 | 0.9091 | |
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| 0.2168 | 26.7717 | 1700 | 0.7417 | 0.9046 | |
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| 0.2112 | 28.3465 | 1800 | 0.7479 | 0.9088 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1.dev0 |
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- Tokenizers 0.19.1 |
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