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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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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-tamil-colab-final |
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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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# wav2vec2-large-xls-r-300m-tamil-colab-final |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7539 |
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- Wer: 0.6135 |
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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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| 11.1466 | 1.0 | 118 | 4.3444 | 1.0 | |
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| 3.4188 | 2.0 | 236 | 3.2496 | 1.0 | |
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| 2.8617 | 3.0 | 354 | 1.6165 | 1.0003 | |
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| 0.958 | 4.0 | 472 | 0.7984 | 0.8720 | |
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| 0.5929 | 5.0 | 590 | 0.6733 | 0.7831 | |
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| 0.4628 | 6.0 | 708 | 0.6536 | 0.7621 | |
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| 0.3834 | 7.0 | 826 | 0.6037 | 0.7155 | |
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| 0.3242 | 8.0 | 944 | 0.6376 | 0.7184 | |
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| 0.2736 | 9.0 | 1062 | 0.6214 | 0.7070 | |
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| 0.2433 | 10.0 | 1180 | 0.6158 | 0.6944 | |
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| 0.2217 | 11.0 | 1298 | 0.6548 | 0.6830 | |
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| 0.1992 | 12.0 | 1416 | 0.6331 | 0.6775 | |
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| 0.1804 | 13.0 | 1534 | 0.6644 | 0.6874 | |
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| 0.1639 | 14.0 | 1652 | 0.6629 | 0.6649 | |
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| 0.143 | 15.0 | 1770 | 0.6927 | 0.6836 | |
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| 0.1394 | 16.0 | 1888 | 0.6933 | 0.6888 | |
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| 0.1296 | 17.0 | 2006 | 0.7039 | 0.6860 | |
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| 0.1212 | 18.0 | 2124 | 0.7042 | 0.6628 | |
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| 0.1121 | 19.0 | 2242 | 0.7132 | 0.6475 | |
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| 0.1069 | 20.0 | 2360 | 0.7423 | 0.6438 | |
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| 0.1063 | 21.0 | 2478 | 0.7171 | 0.6484 | |
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| 0.1025 | 22.0 | 2596 | 0.7396 | 0.6451 | |
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| 0.0946 | 23.0 | 2714 | 0.7400 | 0.6432 | |
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| 0.0902 | 24.0 | 2832 | 0.7385 | 0.6286 | |
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| 0.0828 | 25.0 | 2950 | 0.7368 | 0.6286 | |
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| 0.079 | 26.0 | 3068 | 0.7471 | 0.6306 | |
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| 0.0747 | 27.0 | 3186 | 0.7524 | 0.6201 | |
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| 0.0661 | 28.0 | 3304 | 0.7576 | 0.6201 | |
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| 0.0659 | 29.0 | 3422 | 0.7579 | 0.6130 | |
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| 0.0661 | 30.0 | 3540 | 0.7539 | 0.6135 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.13.3 |
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- Tokenizers 0.10.3 |
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