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---
language:
- lv
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: ''
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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - LV dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1660
- Wer: 0.1705
## 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: 7.5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.489 | 2.56 | 400 | 3.3590 | 1.0 |
| 2.9903 | 5.13 | 800 | 2.9704 | 1.0001 |
| 1.6712 | 7.69 | 1200 | 0.6179 | 0.6566 |
| 1.2635 | 10.26 | 1600 | 0.3176 | 0.4531 |
| 1.0819 | 12.82 | 2000 | 0.2517 | 0.3508 |
| 1.0136 | 15.38 | 2400 | 0.2257 | 0.3124 |
| 0.9625 | 17.95 | 2800 | 0.1975 | 0.2311 |
| 0.901 | 20.51 | 3200 | 0.1986 | 0.2097 |
| 0.8842 | 23.08 | 3600 | 0.1904 | 0.2039 |
| 0.8542 | 25.64 | 4000 | 0.1847 | 0.1981 |
| 0.8244 | 28.21 | 4400 | 0.1805 | 0.1847 |
| 0.7689 | 30.77 | 4800 | 0.1736 | 0.1832 |
| 0.7825 | 33.33 | 5200 | 0.1698 | 0.1821 |
| 0.7817 | 35.9 | 5600 | 0.1758 | 0.1803 |
| 0.7488 | 38.46 | 6000 | 0.1663 | 0.1760 |
| 0.7171 | 41.03 | 6400 | 0.1636 | 0.1721 |
| 0.7222 | 43.59 | 6800 | 0.1663 | 0.1729 |
| 0.7156 | 46.15 | 7200 | 0.1633 | 0.1715 |
| 0.7121 | 48.72 | 7600 | 0.1666 | 0.1718 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
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