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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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metrics: |
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- wer |
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model-index: |
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- name: nyankole_wav2vec2-runpod-unf-large |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mbalireshawal-makerere-university/huggingface/runs/1l4ekc0h) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mbalireshawal-makerere-university/huggingface/runs/1l4ekc0h) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mbalireshawal-makerere-university/huggingface/runs/1l4ekc0h) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mbalireshawal-makerere-university/huggingface/runs/1l4ekc0h) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mbalireshawal-makerere-university/huggingface/runs/1l4ekc0h) |
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# nyankole_wav2vec2-runpod-unf-large |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 830.9091 |
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- Wer: 0.6101 |
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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: 0.0001 |
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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: cosine |
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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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| 7399.694 | 1.0 | 53 | 3616.8877 | 1.0 | |
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| 7452.8927 | 2.0 | 106 | 3606.0696 | 1.0 | |
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| 7321.2547 | 3.0 | 159 | 3614.7188 | 1.0 | |
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| 7283.513 | 4.0 | 212 | 3665.7957 | 1.0 | |
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| 7260.0973 | 5.0 | 265 | 3556.3738 | 1.0 | |
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| 7184.4652 | 6.0 | 318 | 3440.7732 | 1.0 | |
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| 6526.0413 | 7.0 | 371 | 2693.0374 | 1.0 | |
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| 5025.6185 | 8.0 | 424 | 1748.6117 | 0.9985 | |
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| 3761.0044 | 9.0 | 477 | 1390.0330 | 0.8946 | |
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| 3265.3567 | 10.0 | 530 | 1185.7458 | 0.8108 | |
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| 2818.3317 | 11.0 | 583 | 1076.5151 | 0.7582 | |
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| 2666.5274 | 12.0 | 636 | 1016.1800 | 0.7206 | |
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| 2484.5062 | 13.0 | 689 | 1017.9598 | 0.7026 | |
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| 2363.0265 | 14.0 | 742 | 935.6443 | 0.6879 | |
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| 2215.8507 | 15.0 | 795 | 926.4963 | 0.6670 | |
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| 2169.1753 | 16.0 | 848 | 892.7558 | 0.6608 | |
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| 2054.9318 | 17.0 | 901 | 885.1797 | 0.6461 | |
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| 2001.906 | 18.0 | 954 | 869.5634 | 0.6369 | |
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| 2011.2323 | 19.0 | 1007 | 857.0482 | 0.6317 | |
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| 1900.8241 | 20.0 | 1060 | 855.6694 | 0.625 | |
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| 1869.7319 | 21.0 | 1113 | 842.1160 | 0.6296 | |
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| 1809.5601 | 22.0 | 1166 | 838.9195 | 0.6219 | |
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| 1828.7354 | 23.0 | 1219 | 830.1293 | 0.6198 | |
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| 1804.8732 | 24.0 | 1272 | 835.9683 | 0.6173 | |
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| 1775.2409 | 25.0 | 1325 | 831.1539 | 0.6103 | |
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| 1805.726 | 26.0 | 1378 | 831.0961 | 0.6157 | |
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| 1738.365 | 27.0 | 1431 | 831.4120 | 0.6126 | |
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| 1802.3348 | 28.0 | 1484 | 831.5934 | 0.6113 | |
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| 1806.6047 | 29.0 | 1537 | 831.4467 | 0.6101 | |
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| 1788.635 | 30.0 | 1590 | 830.9091 | 0.6101 | |
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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 |
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