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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: xls-r-300-cv17-bulgarian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: bg
split: validation
args: bg
metrics:
- name: Wer
type: wer
value: 0.2967878948765596
---
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# xls-r-300-cv17-bulgarian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4329
- Wer: 0.2968
- Cer: 0.0726
## 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: 0.0003
- 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: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 4.0388 | 0.6579 | 100 | 4.1422 | 1.0 | 1.0 |
| 3.047 | 1.3158 | 200 | 3.0730 | 1.0 | 1.0 |
| 2.7349 | 1.9737 | 300 | 2.7601 | 0.9939 | 0.9946 |
| 0.6047 | 2.6316 | 400 | 0.6984 | 0.7954 | 0.1942 |
| 0.3868 | 3.2895 | 500 | 0.5550 | 0.5994 | 0.1519 |
| 0.3423 | 3.9474 | 600 | 0.4548 | 0.4804 | 0.1195 |
| 0.1942 | 4.6053 | 700 | 0.3973 | 0.4277 | 0.1034 |
| 0.1754 | 5.2632 | 800 | 0.4166 | 0.4391 | 0.1055 |
| 0.1734 | 5.9211 | 900 | 0.4146 | 0.4195 | 0.1018 |
| 0.1089 | 6.5789 | 1000 | 0.3859 | 0.3867 | 0.0937 |
| 0.233 | 7.2368 | 1100 | 0.4183 | 0.4054 | 0.1005 |
| 0.1519 | 7.8947 | 1200 | 0.4459 | 0.4151 | 0.1030 |
| 0.1176 | 8.5526 | 1300 | 0.4026 | 0.3845 | 0.0937 |
| 0.0997 | 9.2105 | 1400 | 0.3849 | 0.3590 | 0.0869 |
| 0.1266 | 9.8684 | 1500 | 0.4281 | 0.3781 | 0.0947 |
| 0.0945 | 10.5263 | 1600 | 0.4471 | 0.3983 | 0.0979 |
| 0.0575 | 11.1842 | 1700 | 0.4290 | 0.3660 | 0.0897 |
| 0.0854 | 11.8421 | 1800 | 0.4258 | 0.3749 | 0.0938 |
| 0.0558 | 12.5 | 1900 | 0.4242 | 0.3644 | 0.0907 |
| 0.0774 | 13.1579 | 2000 | 0.4339 | 0.3616 | 0.0888 |
| 0.0397 | 13.8158 | 2100 | 0.4155 | 0.3581 | 0.0882 |
| 0.0603 | 14.4737 | 2200 | 0.4681 | 0.3737 | 0.0943 |
| 0.0723 | 15.1316 | 2300 | 0.4446 | 0.3560 | 0.0875 |
| 0.0746 | 15.7895 | 2400 | 0.4430 | 0.3573 | 0.0889 |
| 0.0727 | 16.4474 | 2500 | 0.4549 | 0.3470 | 0.0870 |
| 0.0458 | 17.1053 | 2600 | 0.4581 | 0.3520 | 0.0873 |
| 0.0694 | 17.7632 | 2700 | 0.4414 | 0.3575 | 0.0896 |
| 0.0462 | 18.4211 | 2800 | 0.4235 | 0.3261 | 0.0802 |
| 0.0539 | 19.0789 | 2900 | 0.4496 | 0.3329 | 0.0810 |
| 0.0368 | 19.7368 | 3000 | 0.4043 | 0.3406 | 0.0846 |
| 0.0347 | 20.3947 | 3100 | 0.4367 | 0.3225 | 0.0789 |
| 0.019 | 21.0526 | 3200 | 0.4487 | 0.3272 | 0.0801 |
| 0.0361 | 21.7105 | 3300 | 0.4272 | 0.3241 | 0.0785 |
| 0.0475 | 22.3684 | 3400 | 0.4324 | 0.3191 | 0.0781 |
| 0.0341 | 23.0263 | 3500 | 0.4564 | 0.3398 | 0.0847 |
| 0.0454 | 23.6842 | 3600 | 0.4415 | 0.3188 | 0.0789 |
| 0.0346 | 24.3421 | 3700 | 0.4187 | 0.3072 | 0.0751 |
| 0.1315 | 25.0 | 3800 | 0.4480 | 0.3124 | 0.0765 |
| 0.0663 | 25.6579 | 3900 | 0.4488 | 0.3151 | 0.0779 |
| 0.0225 | 26.3158 | 4000 | 0.4372 | 0.3006 | 0.0739 |
| 0.0382 | 26.9737 | 4100 | 0.4164 | 0.2987 | 0.0730 |
| 0.0194 | 27.6316 | 4200 | 0.4190 | 0.2942 | 0.0718 |
| 0.0101 | 28.2895 | 4300 | 0.4328 | 0.2960 | 0.0726 |
| 0.0224 | 28.9474 | 4400 | 0.4302 | 0.2944 | 0.0720 |
| 0.0174 | 29.6053 | 4500 | 0.4329 | 0.2968 | 0.0726 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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