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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xlsr-a-nomimose
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlsr-a-nomimose
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.
It achieves the following results on the evaluation set:
- Loss: 0.4623
- Wer: 0.3473
## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 4.7536 | 1.8387 | 200 | 2.6165 | 1.0 |
| 1.8115 | 3.6728 | 400 | 0.6163 | 0.6689 |
| 0.469 | 5.5069 | 600 | 0.5160 | 0.5442 |
| 0.2745 | 7.3410 | 800 | 0.2917 | 0.4108 |
| 0.1694 | 9.1751 | 1000 | 0.3568 | 0.4624 |
| 0.1782 | 11.0092 | 1200 | 0.3223 | 0.3901 |
| 0.1406 | 12.8479 | 1400 | 0.2959 | 0.3923 |
| 0.1046 | 14.6820 | 1600 | 0.3131 | 0.3658 |
| 0.109 | 16.5161 | 1800 | 0.3343 | 0.3739 |
| 0.1135 | 18.3502 | 2000 | 0.3368 | 0.3577 |
| 0.0875 | 20.1843 | 2200 | 0.4722 | 0.3695 |
| 0.0956 | 22.0184 | 2400 | 0.3427 | 0.3614 |
| 0.0749 | 23.8571 | 2600 | 0.3377 | 0.3695 |
| 0.0727 | 25.6912 | 2800 | 0.3489 | 0.3599 |
| 0.0655 | 27.5253 | 3000 | 0.3348 | 0.3665 |
| 0.0603 | 29.3594 | 3200 | 0.3636 | 0.3606 |
| 0.0537 | 31.1935 | 3400 | 0.3923 | 0.3555 |
| 0.0567 | 33.0276 | 3600 | 0.3476 | 0.3555 |
| 0.0461 | 34.8664 | 3800 | 0.3589 | 0.3628 |
| 0.0459 | 36.7005 | 4000 | 0.4104 | 0.3584 |
| 0.0467 | 38.5346 | 4200 | 0.3686 | 0.3555 |
| 0.0419 | 40.3687 | 4400 | 0.3889 | 0.3555 |
| 0.0381 | 42.2028 | 4600 | 0.4013 | 0.3540 |
| 0.0403 | 44.0369 | 4800 | 0.4077 | 0.3555 |
| 0.0371 | 45.8756 | 5000 | 0.4502 | 0.3577 |
| 0.0354 | 47.7097 | 5200 | 0.4884 | 0.3739 |
| 0.0372 | 49.5438 | 5400 | 0.4227 | 0.3614 |
| 0.0344 | 51.3779 | 5600 | 0.3949 | 0.3532 |
| 0.0288 | 53.2120 | 5800 | 0.4088 | 0.3532 |
| 0.0314 | 55.0461 | 6000 | 0.4194 | 0.3496 |
| 0.0276 | 56.8848 | 6200 | 0.4184 | 0.3532 |
| 0.0232 | 58.7189 | 6400 | 0.4184 | 0.3496 |
| 0.0267 | 60.5530 | 6600 | 0.4028 | 0.3496 |
| 0.0271 | 62.3871 | 6800 | 0.3804 | 0.3488 |
| 0.0205 | 64.2212 | 7000 | 0.4735 | 0.3466 |
| 0.0243 | 66.0553 | 7200 | 0.4108 | 0.3473 |
| 0.0198 | 67.8940 | 7400 | 0.4157 | 0.3488 |
| 0.0193 | 69.7281 | 7600 | 0.4226 | 0.3547 |
| 0.0222 | 71.5622 | 7800 | 0.4147 | 0.3451 |
| 0.0176 | 73.3963 | 8000 | 0.4553 | 0.3488 |
| 0.0209 | 75.2304 | 8200 | 0.4135 | 0.3525 |
| 0.0222 | 77.0645 | 8400 | 0.4300 | 0.3481 |
| 0.0169 | 78.9032 | 8600 | 0.4139 | 0.3481 |
| 0.0174 | 80.7373 | 8800 | 0.4510 | 0.3473 |
| 0.019 | 82.5714 | 9000 | 0.4664 | 0.3488 |
| 0.0145 | 84.4055 | 9200 | 0.4768 | 0.3459 |
| 0.0146 | 86.2396 | 9400 | 0.4678 | 0.3466 |
| 0.0184 | 88.0737 | 9600 | 0.4906 | 0.3488 |
| 0.0141 | 89.9124 | 9800 | 0.4676 | 0.3481 |
| 0.0128 | 91.7465 | 10000 | 0.4612 | 0.3473 |
| 0.0134 | 93.5806 | 10200 | 0.4649 | 0.3459 |
| 0.0134 | 95.4147 | 10400 | 0.4606 | 0.3481 |
| 0.0126 | 97.2488 | 10600 | 0.4646 | 0.3488 |
| 0.014 | 99.0829 | 10800 | 0.4623 | 0.3473 |
### Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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