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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-hun-53h-colab
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. -->
# wav2vec2-large-xls-hun-53h-colab
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6027
- Wer: 0.4618
## 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: 23
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 13.4225 | 0.67 | 100 | 3.7750 | 1.0 |
| 3.4121 | 1.34 | 200 | 3.3166 | 1.0 |
| 3.2263 | 2.01 | 300 | 3.1403 | 1.0 |
| 3.0038 | 2.68 | 400 | 2.2474 | 0.9990 |
| 1.2243 | 3.35 | 500 | 0.8174 | 0.7666 |
| 0.6368 | 4.03 | 600 | 0.6306 | 0.6633 |
| 0.4426 | 4.7 | 700 | 0.6151 | 0.6648 |
| 0.3821 | 5.37 | 800 | 0.5765 | 0.6138 |
| 0.3337 | 6.04 | 900 | 0.5522 | 0.5785 |
| 0.2832 | 6.71 | 1000 | 0.5822 | 0.5691 |
| 0.2485 | 7.38 | 1100 | 0.5626 | 0.5449 |
| 0.2335 | 8.05 | 1200 | 0.5866 | 0.5662 |
| 0.2031 | 8.72 | 1300 | 0.5574 | 0.5420 |
| 0.1925 | 9.39 | 1400 | 0.5572 | 0.5297 |
| 0.1793 | 10.07 | 1500 | 0.5878 | 0.5185 |
| 0.1652 | 10.74 | 1600 | 0.6173 | 0.5243 |
| 0.1663 | 11.41 | 1700 | 0.5807 | 0.5133 |
| 0.1544 | 12.08 | 1800 | 0.5979 | 0.5154 |
| 0.148 | 12.75 | 1900 | 0.5545 | 0.4986 |
| 0.138 | 13.42 | 2000 | 0.5798 | 0.4947 |
| 0.1353 | 14.09 | 2100 | 0.5670 | 0.5028 |
| 0.1283 | 14.76 | 2200 | 0.5862 | 0.4957 |
| 0.1271 | 15.43 | 2300 | 0.6009 | 0.4961 |
| 0.1108 | 16.11 | 2400 | 0.5873 | 0.4975 |
| 0.1182 | 16.78 | 2500 | 0.6013 | 0.4893 |
| 0.103 | 17.45 | 2600 | 0.6165 | 0.4898 |
| 0.1084 | 18.12 | 2700 | 0.6186 | 0.4838 |
| 0.1014 | 18.79 | 2800 | 0.6122 | 0.4767 |
| 0.1009 | 19.46 | 2900 | 0.5981 | 0.4793 |
| 0.1004 | 20.13 | 3000 | 0.6034 | 0.4770 |
| 0.0922 | 20.8 | 3100 | 0.6127 | 0.4663 |
| 0.09 | 21.47 | 3200 | 0.5967 | 0.4672 |
| 0.0893 | 22.15 | 3300 | 0.6051 | 0.4611 |
| 0.0817 | 22.82 | 3400 | 0.6027 | 0.4618 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3
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