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---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
- cer
model-index:
- name: wav2vec2-large-xls-r-1b-Swedish
results:
- task:
type: automatic-speech-recognition # Required. Example: automatic-speech-recognition
name: Speech Recognition # Optional. Example: Speech Recognition
dataset:
type: mozilla-foundation/common_voice_8_0 # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
name: Common Voice sv-SE # Required. Example: Common Voice zh-CN
args: sv-SE # Optional. Example: zh-CN
metrics:
- type: wer # Required. Example: wer
value: 18.03 # Required. Example: 20.90
name: Test WER Without LM # Optional. Example: Test WER
args:
- learning_rate: 7.5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
- mixed_precision_training: Native AMP # Optional. Example for BLEU: max_order
- type: cer # Required. Example: wer
value: 5.69 # Required. Example: 20.90
name: Test CER Without LM # Optional. Example: Test WER
args:
- learning_rate: 7.5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
- mixed_precision_training: Native AMP
---
<!-- 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-1b-Swedish
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset.
It achieves the following results on the evaluation set:
**Without LM**
- Loss: 0.3370
- Wer: 0.1803
- Cer: 0.0569
**With LM**
## 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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.1423 | 5.49 | 500 | 0.5523 | 0.4414 | 0.1313 |
| 0.8615 | 10.98 | 1000 | 0.3877 | 0.2946 | 0.0942 |
| 0.4848 | 16.48 | 1500 | 0.3580 | 0.2539 | 0.0798 |
| 0.3538 | 21.97 | 2000 | 0.3391 | 0.2254 | 0.0709 |
| 0.2879 | 27.47 | 2500 | 0.3392 | 0.2151 | 0.0680 |
| 0.2466 | 32.96 | 3000 | 0.3687 | 0.2131 | 0.0680 |
| 0.2146 | 38.46 | 3500 | 0.3551 | 0.1951 | 0.0618 |
| 0.1916 | 43.95 | 4000 | 0.3601 | 0.1867 | 0.0590 |
| 0.175 | 49.45 | 4500 | 0.3370 | 0.1803 | 0.0569 |
### 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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