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---
language:
- hsb
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- hsb
- robust-speech-event
- model_for_talk
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: wav2vec2-large-xls-r-300m-hsb-v2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: hsb
metrics:
- name: Test WER
type: wer
value: []
- name: Test CER
type: cer
value: []
---
<!-- 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-r-300m-hsb-v2
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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5328
- Wer: 0.4596
## 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: 0.00045
- 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: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.5979 | 3.23 | 100 | 3.5602 | 1.0 |
| 3.303 | 6.45 | 200 | 3.2238 | 1.0 |
| 3.2034 | 9.68 | 300 | 3.2002 | 0.9888 |
| 2.7986 | 12.9 | 400 | 1.2408 | 0.9210 |
| 1.3869 | 16.13 | 500 | 0.7973 | 0.7462 |
| 1.0228 | 19.35 | 600 | 0.6722 | 0.6788 |
| 0.8311 | 22.58 | 700 | 0.6100 | 0.6150 |
| 0.717 | 25.81 | 800 | 0.6236 | 0.6013 |
| 0.6264 | 29.03 | 900 | 0.6031 | 0.5575 |
| 0.5494 | 32.26 | 1000 | 0.5656 | 0.5309 |
| 0.4781 | 35.48 | 1100 | 0.5289 | 0.4996 |
| 0.4311 | 38.71 | 1200 | 0.5375 | 0.4768 |
| 0.3902 | 41.94 | 1300 | 0.5246 | 0.4703 |
| 0.3508 | 45.16 | 1400 | 0.5382 | 0.4696 |
| 0.3199 | 48.39 | 1500 | 0.5328 | 0.4596 |
### Framework versions
- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0
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