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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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- thennal/IMaSC |
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- vrclc/openslr63 |
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- thennal/indic_tts_ml |
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- kavyamanohar/ml-sentences |
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model-index: |
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- name: XLSR-WithLM-Malayalam |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: OpenSLR Malayalam -Test |
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type: vrclc/openslr63 |
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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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- type: wer |
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value: 27.3 |
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name: WER |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: Goole Fleurs |
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type: google/fleurs |
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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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- type: wer |
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value: 37.2 |
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name: WER |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: MSC |
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type: smcproject/msc |
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config: ml |
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split: train |
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args: ml |
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metrics: |
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- type: wer |
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value: 52.9 |
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name: WER |
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--- |
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# XLSR-WithLM-Malayalam |
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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 [IMASC](https://huggingface.co/datasets/thennal/IMaSC), [Indic TTS Malayalam](https://huggingface.co/datasets/thennal/indic_tts_ml), [OpenSLR Malayalam Train split](https://huggingface.co/datasets/vrclc/openslr63) datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1395 |
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- Wer: 0.2952 |
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Trigram Language Model Trained using KENLM Library on [kavyamanohar/ml-sentences](https://huggingface.co/datasets/kavyamanohar/ml-sentences) dataset |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.00024 |
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- train_batch_size: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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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: 800 |
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- num_epochs: 1 |
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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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| 1.4912 | 0.1165 | 1000 | 0.5497 | 0.7011 | |
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| 0.5377 | 0.2330 | 2000 | 0.3292 | 0.5364 | |
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| 0.4343 | 0.3494 | 3000 | 0.2475 | 0.4424 | |
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| 0.3678 | 0.4659 | 4000 | 0.2145 | 0.4014 | |
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| 0.3345 | 0.5824 | 5000 | 0.1898 | 0.3774 | |
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| 0.3029 | 0.6989 | 6000 | 0.1718 | 0.3441 | |
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| 0.2685 | 0.8153 | 7000 | 0.1517 | 0.3135 | |
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| 0.2385 | 0.9318 | 8000 | 0.1395 | 0.2952 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
