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--- |
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license: apache-2.0 |
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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: HO_ASR-Model_KIIT2025 |
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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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# HO_ASR-Model_KIIT2025 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6844 |
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- Wer: 0.5516 |
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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: 5e-05 |
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- train_batch_size: 32 |
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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: 64 |
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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: 250 |
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- num_epochs: 50 |
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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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| 2.9609 | 2.0 | 250 | 2.8620 | 0.9958 | |
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| 2.3792 | 4.0 | 500 | 1.5657 | 0.8976 | |
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| 0.8142 | 6.0 | 750 | 0.8104 | 0.7383 | |
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| 0.5211 | 8.0 | 1000 | 0.6461 | 0.6508 | |
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| 0.4145 | 10.0 | 1250 | 0.5793 | 0.6257 | |
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| 0.3562 | 12.0 | 1500 | 0.5991 | 0.6315 | |
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| 0.3135 | 14.0 | 1750 | 0.5680 | 0.6295 | |
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| 0.2694 | 16.0 | 2000 | 0.5731 | 0.6139 | |
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| 0.2333 | 18.0 | 2250 | 0.6170 | 0.6482 | |
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| 0.2061 | 20.0 | 2500 | 0.5771 | 0.5852 | |
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| 0.1823 | 22.0 | 2750 | 0.5820 | 0.5776 | |
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| 0.1628 | 24.0 | 3000 | 0.5853 | 0.5793 | |
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| 0.1434 | 26.0 | 3250 | 0.6188 | 0.5776 | |
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| 0.129 | 28.0 | 3500 | 0.6095 | 0.5644 | |
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| 0.1185 | 30.0 | 3750 | 0.6210 | 0.5753 | |
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| 0.1071 | 32.0 | 4000 | 0.6250 | 0.5680 | |
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| 0.097 | 34.0 | 4250 | 0.6207 | 0.5636 | |
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| 0.0901 | 36.0 | 4500 | 0.6477 | 0.5760 | |
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| 0.0833 | 38.0 | 4750 | 0.6510 | 0.5666 | |
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| 0.0758 | 40.0 | 5000 | 0.6519 | 0.5553 | |
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| 0.0693 | 42.0 | 5250 | 0.6641 | 0.5549 | |
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| 0.0637 | 44.0 | 5500 | 0.6648 | 0.5490 | |
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| 0.0591 | 46.0 | 5750 | 0.6809 | 0.5535 | |
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| 0.0585 | 48.0 | 6000 | 0.6786 | 0.5512 | |
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| 0.0555 | 50.0 | 6250 | 0.6844 | 0.5516 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.13.3 |
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