End of training
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README.md
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---
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library_name: transformers
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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: wav2vec2-large-xlsr-sorani-v1
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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-xlsr-sorani-v1
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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 the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2492
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- Wer: 0.3566
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 15
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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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| 9.2607 | 0.3543 | 200 | 6.4854 | 1.0 |
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| 3.0716 | 0.7086 | 400 | 3.0408 | 1.0 |
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| 2.8638 | 1.0620 | 600 | 2.8982 | 1.0 |
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| 2.8666 | 1.4163 | 800 | 2.8511 | 1.0 |
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| 1.8111 | 1.7706 | 1000 | 1.5181 | 1.0095 |
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| 0.7703 | 2.1240 | 1200 | 0.5528 | 0.6563 |
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| 0.6864 | 2.4783 | 1400 | 0.4600 | 0.5909 |
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| 0.5955 | 2.8326 | 1600 | 0.4036 | 0.5362 |
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| 0.4894 | 3.1860 | 1800 | 0.3811 | 0.5030 |
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| 0.5007 | 3.5403 | 2000 | 0.3551 | 0.4782 |
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| 0.5169 | 3.8946 | 2200 | 0.3340 | 0.4627 |
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| 0.4613 | 4.2480 | 2400 | 0.3271 | 0.4527 |
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| 0.4499 | 4.6023 | 2600 | 0.3229 | 0.4437 |
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| 0.4093 | 4.9566 | 2800 | 0.3042 | 0.4333 |
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| 0.4458 | 5.3100 | 3000 | 0.3040 | 0.4316 |
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| 0.4107 | 5.6643 | 3200 | 0.2875 | 0.4162 |
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| 0.3728 | 6.0177 | 3400 | 0.2862 | 0.4150 |
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| 0.348 | 6.3720 | 3600 | 0.2939 | 0.4068 |
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| 0.3393 | 6.7263 | 3800 | 0.2755 | 0.3977 |
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| 0.3572 | 7.0797 | 4000 | 0.2799 | 0.3975 |
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| 0.3453 | 7.4340 | 4200 | 0.2748 | 0.3975 |
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| 0.3434 | 7.7883 | 4400 | 0.2688 | 0.3907 |
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| 0.3231 | 8.1417 | 4600 | 0.2706 | 0.3871 |
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| 0.3148 | 8.4960 | 4800 | 0.2688 | 0.3830 |
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| 0.3261 | 8.8503 | 5000 | 0.2625 | 0.3811 |
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| 0.3055 | 9.2037 | 5200 | 0.2597 | 0.3719 |
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| 0.3028 | 9.5580 | 5400 | 0.2593 | 0.3720 |
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| 0.3246 | 9.9123 | 5600 | 0.2535 | 0.3724 |
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| 0.274 | 10.2657 | 5800 | 0.2551 | 0.3690 |
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| 0.2832 | 10.6200 | 6000 | 0.2601 | 0.3716 |
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| 0.2899 | 10.9743 | 6200 | 0.2521 | 0.3670 |
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| 0.2889 | 11.3277 | 6400 | 0.2574 | 0.3652 |
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| 0.2675 | 11.6820 | 6600 | 0.2564 | 0.3611 |
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| 0.3334 | 12.0354 | 6800 | 0.2548 | 0.3603 |
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| 0.2568 | 12.3897 | 7000 | 0.2538 | 0.3606 |
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| 0.2842 | 12.7440 | 7200 | 0.2566 | 0.3597 |
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| 0.2631 | 13.0974 | 7400 | 0.2540 | 0.3580 |
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| 0.2573 | 13.4517 | 7600 | 0.2513 | 0.3569 |
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| 0.27 | 13.8060 | 7800 | 0.2499 | 0.3556 |
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| 0.2578 | 14.1594 | 8000 | 0.2496 | 0.3556 |
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| 0.2528 | 14.5137 | 8200 | 0.2498 | 0.3565 |
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| 0.2644 | 14.8680 | 8400 | 0.2492 | 0.3566 |
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### Framework versions
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- Transformers 4.54.1
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- Pytorch 2.7.1+cu128
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- Datasets 3.6.0
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- Tokenizers 0.21.4
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