--- license: apache-2.0 base_model: facebook/wav2vec2-xls-r-300m tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-xlsr-ln-5hr-v1 results: [] --- [Visualize in Weights & Biases](https://wandb.ai/asr-africa-research-team/ASR%20Africa/runs/hepb2xqx) # wav2vec2-xlsr-ln-5hr-v1 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. It achieves the following results on the evaluation set: - Loss: 0.5624 - Model Preparation Time: 0.0057 - Wer: 0.2571 - Cer: 0.0734 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 500 - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer | |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:------:| | 16.386 | 1.0 | 69 | 12.2905 | 0.0057 | 1.0 | 1.0 | | 5.5203 | 2.0 | 138 | 3.9569 | 0.0057 | 1.0 | 1.0 | | 3.4 | 3.0 | 207 | 3.1451 | 0.0057 | 1.0 | 1.0 | | 2.9614 | 4.0 | 276 | 2.8816 | 0.0057 | 1.0 | 1.0 | | 2.8304 | 5.0 | 345 | 2.8508 | 0.0057 | 1.0 | 1.0 | | 2.3503 | 6.0 | 414 | 1.4634 | 0.0057 | 0.9609 | 0.3336 | | 0.9982 | 7.0 | 483 | 0.7307 | 0.0057 | 0.4987 | 0.1411 | | 0.6755 | 8.0 | 552 | 0.6046 | 0.0057 | 0.4915 | 0.1328 | | 0.5294 | 9.0 | 621 | 0.5178 | 0.0057 | 0.4908 | 0.1236 | | 0.4127 | 10.0 | 690 | 0.4592 | 0.0057 | 0.3672 | 0.1024 | | 0.351 | 11.0 | 759 | 0.4412 | 0.0057 | 0.3898 | 0.1115 | | 0.2951 | 12.0 | 828 | 0.4443 | 0.0057 | 0.3696 | 0.1158 | | 0.2652 | 13.0 | 897 | 0.4260 | 0.0057 | 0.3569 | 0.0966 | | 0.2294 | 14.0 | 966 | 0.3866 | 0.0057 | 0.3242 | 0.0929 | | 0.2015 | 15.0 | 1035 | 0.4026 | 0.0057 | 0.3110 | 0.0881 | | 0.1806 | 16.0 | 1104 | 0.3866 | 0.0057 | 0.3048 | 0.0869 | | 0.1593 | 17.0 | 1173 | 0.4070 | 0.0057 | 0.3133 | 0.0899 | | 0.1427 | 18.0 | 1242 | 0.4013 | 0.0057 | 0.3108 | 0.0877 | | 0.1285 | 19.0 | 1311 | 0.4124 | 0.0057 | 0.2983 | 0.0861 | | 0.1223 | 20.0 | 1380 | 0.4172 | 0.0057 | 0.3173 | 0.0919 | | 0.109 | 21.0 | 1449 | 0.4232 | 0.0057 | 0.2934 | 0.0844 | | 0.109 | 22.0 | 1518 | 0.4238 | 0.0057 | 0.2952 | 0.0879 | | 0.0935 | 23.0 | 1587 | 0.4662 | 0.0057 | 0.2797 | 0.0834 | | 0.095 | 24.0 | 1656 | 0.4323 | 0.0057 | 0.2780 | 0.0824 | | 0.0797 | 25.0 | 1725 | 0.4363 | 0.0057 | 0.2809 | 0.0823 | | 0.0795 | 26.0 | 1794 | 0.4421 | 0.0057 | 0.2925 | 0.0835 | | 0.0718 | 27.0 | 1863 | 0.4394 | 0.0057 | 0.2887 | 0.0848 | | 0.071 | 28.0 | 1932 | 0.4397 | 0.0057 | 0.2773 | 0.0810 | | 0.066 | 29.0 | 2001 | 0.4639 | 0.0057 | 0.2755 | 0.0817 | | 0.0598 | 30.0 | 2070 | 0.4674 | 0.0057 | 0.2844 | 0.0828 | | 0.0609 | 31.0 | 2139 | 0.4663 | 0.0057 | 0.2771 | 0.0836 | | 0.0532 | 32.0 | 2208 | 0.4848 | 0.0057 | 0.2860 | 0.0836 | | 0.0549 | 33.0 | 2277 | 0.4718 | 0.0057 | 0.2701 | 0.0797 | | 0.0523 | 34.0 | 2346 | 0.4618 | 0.0057 | 0.2699 | 0.0792 | | 0.049 | 35.0 | 2415 | 0.4866 | 0.0057 | 0.2679 | 0.0785 | | 0.052 | 36.0 | 2484 | 0.4683 | 0.0057 | 0.2643 | 0.0781 | | 0.0439 | 37.0 | 2553 | 0.4814 | 0.0057 | 0.2627 | 0.0794 | | 0.0411 | 38.0 | 2622 | 0.4893 | 0.0057 | 0.2703 | 0.0786 | | 0.0411 | 39.0 | 2691 | 0.4894 | 0.0057 | 0.2724 | 0.0788 | | 0.0408 | 40.0 | 2760 | 0.4604 | 0.0057 | 0.2619 | 0.0781 | | 0.0411 | 41.0 | 2829 | 0.4763 | 0.0057 | 0.2572 | 0.0778 | | 0.0391 | 42.0 | 2898 | 0.4911 | 0.0057 | 0.2650 | 0.0778 | | 0.0402 | 43.0 | 2967 | 0.4649 | 0.0057 | 0.2650 | 0.0786 | | 0.0363 | 44.0 | 3036 | 0.4865 | 0.0057 | 0.2589 | 0.0784 | | 0.0318 | 45.0 | 3105 | 0.5020 | 0.0057 | 0.2585 | 0.0784 | | 0.0319 | 46.0 | 3174 | 0.4973 | 0.0057 | 0.2683 | 0.0785 | | 0.0292 | 47.0 | 3243 | 0.5007 | 0.0057 | 0.2585 | 0.0784 | | 0.0294 | 48.0 | 3312 | 0.5059 | 0.0057 | 0.2587 | 0.0768 | | 0.0305 | 49.0 | 3381 | 0.5039 | 0.0057 | 0.2665 | 0.0783 | | 0.0309 | 50.0 | 3450 | 0.4968 | 0.0057 | 0.2641 | 0.0783 | | 0.0277 | 51.0 | 3519 | 0.5287 | 0.0057 | 0.2659 | 0.0771 | | 0.024 | 52.0 | 3588 | 0.4998 | 0.0057 | 0.2558 | 0.0758 | | 0.0243 | 53.0 | 3657 | 0.4997 | 0.0057 | 0.2603 | 0.0760 | | 0.0255 | 54.0 | 3726 | 0.4989 | 0.0057 | 0.2563 | 0.0764 | | 0.0233 | 55.0 | 3795 | 0.5191 | 0.0057 | 0.2587 | 0.0768 | | 0.0247 | 56.0 | 3864 | 0.5036 | 0.0057 | 0.2487 | 0.0753 | | 0.0224 | 57.0 | 3933 | 0.5060 | 0.0057 | 0.2489 | 0.0750 | | 0.024 | 58.0 | 4002 | 0.4976 | 0.0057 | 0.2482 | 0.0755 | | 0.0259 | 59.0 | 4071 | 0.5163 | 0.0057 | 0.2587 | 0.0754 | | 0.0217 | 60.0 | 4140 | 0.5191 | 0.0057 | 0.2496 | 0.0747 | | 0.0218 | 61.0 | 4209 | 0.5035 | 0.0057 | 0.2502 | 0.0748 | | 0.0199 | 62.0 | 4278 | 0.5277 | 0.0057 | 0.2460 | 0.0741 | | 0.0176 | 63.0 | 4347 | 0.5205 | 0.0057 | 0.2442 | 0.0747 | | 0.0189 | 64.0 | 4416 | 0.5152 | 0.0057 | 0.2451 | 0.0744 | | 0.0184 | 65.0 | 4485 | 0.5061 | 0.0057 | 0.2399 | 0.0734 | | 0.018 | 66.0 | 4554 | 0.5243 | 0.0057 | 0.2422 | 0.0732 | | 0.0186 | 67.0 | 4623 | 0.5180 | 0.0057 | 0.2480 | 0.0751 | | 0.0158 | 68.0 | 4692 | 0.5269 | 0.0057 | 0.2449 | 0.0743 | | 0.0159 | 69.0 | 4761 | 0.5240 | 0.0057 | 0.2431 | 0.0750 | | 0.0149 | 70.0 | 4830 | 0.5255 | 0.0057 | 0.2413 | 0.0738 | | 0.0132 | 71.0 | 4899 | 0.5365 | 0.0057 | 0.2442 | 0.0744 | | 0.0135 | 72.0 | 4968 | 0.5250 | 0.0057 | 0.2433 | 0.0735 | | 0.014 | 73.0 | 5037 | 0.5241 | 0.0057 | 0.2442 | 0.0735 | | 0.0144 | 74.0 | 5106 | 0.5267 | 0.0057 | 0.2466 | 0.0735 | | 0.0141 | 75.0 | 5175 | 0.5254 | 0.0057 | 0.2471 | 0.0730 | | 0.0125 | 76.0 | 5244 | 0.5269 | 0.0057 | 0.2440 | 0.0730 | | 0.0116 | 77.0 | 5313 | 0.5310 | 0.0057 | 0.2424 | 0.0734 | | 0.015 | 78.0 | 5382 | 0.5198 | 0.0057 | 0.2419 | 0.0732 | | 0.0113 | 79.0 | 5451 | 0.5275 | 0.0057 | 0.2415 | 0.0733 | | 0.0128 | 80.0 | 5520 | 0.5222 | 0.0057 | 0.2431 | 0.0736 | | 0.0114 | 81.0 | 5589 | 0.5249 | 0.0057 | 0.2384 | 0.0731 | | 0.01 | 82.0 | 5658 | 0.5235 | 0.0057 | 0.2375 | 0.0726 | | 0.0117 | 83.0 | 5727 | 0.5226 | 0.0057 | 0.2408 | 0.0730 | | 0.0105 | 84.0 | 5796 | 0.5205 | 0.0057 | 0.2428 | 0.0738 | | 0.0106 | 85.0 | 5865 | 0.5238 | 0.0057 | 0.2384 | 0.0729 | | 0.0109 | 86.0 | 5934 | 0.5210 | 0.0057 | 0.2379 | 0.0727 | | 0.01 | 87.0 | 6003 | 0.5256 | 0.0057 | 0.2397 | 0.0731 | | 0.01 | 88.0 | 6072 | 0.5305 | 0.0057 | 0.2415 | 0.0735 | | 0.0088 | 89.0 | 6141 | 0.5329 | 0.0057 | 0.2390 | 0.0731 | | 0.0098 | 90.0 | 6210 | 0.5328 | 0.0057 | 0.2393 | 0.0738 | | 0.0089 | 91.0 | 6279 | 0.5348 | 0.0057 | 0.2393 | 0.0736 | | 0.0084 | 92.0 | 6348 | 0.5358 | 0.0057 | 0.2377 | 0.0732 | | 0.0087 | 93.0 | 6417 | 0.5356 | 0.0057 | 0.2388 | 0.0734 | | 0.0104 | 94.0 | 6486 | 0.5338 | 0.0057 | 0.2381 | 0.0732 | | 0.01 | 95.0 | 6555 | 0.5344 | 0.0057 | 0.2384 | 0.0734 | | 0.0103 | 96.0 | 6624 | 0.5343 | 0.0057 | 0.2381 | 0.0734 | | 0.0091 | 97.0 | 6693 | 0.5346 | 0.0057 | 0.2381 | 0.0734 | | 0.0092 | 98.0 | 6762 | 0.5347 | 0.0057 | 0.2381 | 0.0734 | | 0.0098 | 99.0 | 6831 | 0.5348 | 0.0057 | 0.2379 | 0.0734 | | 0.0099 | 100.0 | 6900 | 0.5348 | 0.0057 | 0.2381 | 0.0734 | ### Framework versions - Transformers 4.43.1 - Pytorch 2.2.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1