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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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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-xls-r-300m-malayalam-colab-CV17.0 |
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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: test |
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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: 1.0029013539651837 |
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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-xls-r-300m-malayalam-colab-CV17.0 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) 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: 1.6154 |
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- Wer: 1.0029 |
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- Cer: 0.4254 |
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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: 3e-05 |
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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_ratio: 0.15 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 15.7515 | 3.1496 | 200 | 7.2856 | 1.0 | 1.0 | |
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| 5.2078 | 6.2992 | 400 | 3.9581 | 1.0 | 1.0 | |
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| 3.6268 | 9.4488 | 600 | 3.4876 | 1.0 | 0.9923 | |
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| 3.4082 | 12.5984 | 800 | 3.3891 | 1.0 | 0.9906 | |
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| 3.3259 | 15.7480 | 1000 | 3.3171 | 0.9984 | 0.9415 | |
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| 3.0224 | 18.8976 | 1200 | 2.6551 | 1.0 | 0.7845 | |
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| 2.1063 | 22.0472 | 1400 | 1.9206 | 0.9942 | 0.4722 | |
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| 1.564 | 25.1969 | 1600 | 1.6999 | 0.9916 | 0.4298 | |
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| 1.3323 | 28.3465 | 1800 | 1.6358 | 0.9990 | 0.4264 | |
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| 1.2413 | 31.4961 | 2000 | 1.6154 | 1.0029 | 0.4254 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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