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---
language:
- hy-AM
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- hy
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 - HY-AM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5891
- Wer: 0.6569
**Note**: If you aim for best performance use [this model](https://huggingface.co/arampacha/wav2vec2-xls-r-300m-hy). It is trained using noizy student procedure and achieves considerably better results.
## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1200
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 9.167 | 16.67 | 100 | 3.5599 | 1.0 |
| 3.2645 | 33.33 | 200 | 3.1771 | 1.0 |
| 3.1509 | 50.0 | 300 | 3.1321 | 1.0 |
| 3.0757 | 66.67 | 400 | 2.8594 | 1.0 |
| 2.5274 | 83.33 | 500 | 1.5286 | 0.9797 |
| 1.6826 | 100.0 | 600 | 0.8058 | 0.7974 |
| 1.2868 | 116.67 | 700 | 0.6713 | 0.7279 |
| 1.1262 | 133.33 | 800 | 0.6308 | 0.7034 |
| 1.0408 | 150.0 | 900 | 0.6056 | 0.6745 |
| 0.9617 | 166.67 | 1000 | 0.5891 | 0.6569 |
| 0.9196 | 183.33 | 1100 | 0.5913 | 0.6432 |
| 0.8853 | 200.0 | 1200 | 0.5924 | 0.6347 |
### 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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