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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-nm-nomi
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-nm-nomi
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: 0.3324
- Wer: 0.3245
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.9773 | 6.0606 | 200 | 3.0522 | 1.0 |
| 2.8875 | 12.1212 | 400 | 2.3569 | 0.9959 |
| 1.5131 | 18.1818 | 600 | 0.5795 | 0.6024 |
| 0.4675 | 24.2424 | 800 | 0.4022 | 0.4523 |
| 0.2474 | 30.3030 | 1000 | 0.3396 | 0.4422 |
| 0.1573 | 36.3636 | 1200 | 0.3188 | 0.3611 |
| 0.1162 | 42.4242 | 1400 | 0.3450 | 0.3570 |
| 0.0858 | 48.4848 | 1600 | 0.3162 | 0.3469 |
| 0.0675 | 54.5455 | 1800 | 0.2832 | 0.3327 |
| 0.058 | 60.6061 | 2000 | 0.2904 | 0.3266 |
| 0.0415 | 66.6667 | 2200 | 0.3555 | 0.3306 |
| 0.0348 | 72.7273 | 2400 | 0.3116 | 0.3327 |
| 0.0234 | 78.7879 | 2600 | 0.2944 | 0.3245 |
| 0.0215 | 84.8485 | 2800 | 0.3259 | 0.3266 |
| 0.0208 | 90.9091 | 3000 | 0.3312 | 0.3185 |
| 0.0168 | 96.9697 | 3200 | 0.3324 | 0.3245 |
### Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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