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---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- sv
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R-300M - Swedish - CV8 - v2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: sv-SE
metrics:
- name: Test WER
type: wer
value: 17.33
- name: Test CER
type: cer
value: 5.8
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: sv
metrics:
- name: Test WER
type: wer
value: 27.01
- name: Test CER
type: cer
value: 12.92
---
<!-- 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 - SV-SE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2779
- Wer: 0.2525
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.3224 | 1.37 | 500 | 3.3354 | 1.0 |
| 2.9318 | 2.74 | 1000 | 2.9361 | 1.0000 |
| 2.1371 | 4.11 | 1500 | 1.1157 | 0.8359 |
| 1.6883 | 5.48 | 2000 | 0.6003 | 0.6314 |
| 1.5812 | 6.85 | 2500 | 0.4746 | 0.4725 |
| 1.5145 | 8.22 | 3000 | 0.4376 | 0.4736 |
| 1.4763 | 9.59 | 3500 | 0.4006 | 0.3863 |
| 1.4215 | 10.96 | 4000 | 0.3783 | 0.3629 |
| 1.3638 | 12.33 | 4500 | 0.3555 | 0.3425 |
| 1.3561 | 13.7 | 5000 | 0.3340 | 0.3228 |
| 1.3406 | 15.07 | 5500 | 0.3373 | 0.3295 |
| 1.3055 | 16.44 | 6000 | 0.3432 | 0.3210 |
| 1.3048 | 17.81 | 6500 | 0.3282 | 0.3118 |
| 1.2863 | 19.18 | 7000 | 0.3226 | 0.3018 |
| 1.2389 | 20.55 | 7500 | 0.3050 | 0.2986 |
| 1.2361 | 21.92 | 8000 | 0.3048 | 0.2980 |
| 1.2263 | 23.29 | 8500 | 0.3011 | 0.2977 |
| 1.2225 | 24.66 | 9000 | 0.3017 | 0.2959 |
| 1.2044 | 26.03 | 9500 | 0.2977 | 0.2782 |
| 1.2017 | 27.4 | 10000 | 0.2966 | 0.2781 |
| 1.1912 | 28.77 | 10500 | 0.2999 | 0.2786 |
| 1.1658 | 30.14 | 11000 | 0.2991 | 0.2757 |
| 1.148 | 31.51 | 11500 | 0.2915 | 0.2684 |
| 1.1423 | 32.88 | 12000 | 0.2913 | 0.2643 |
| 1.123 | 34.25 | 12500 | 0.2777 | 0.2630 |
| 1.1297 | 35.62 | 13000 | 0.2873 | 0.2646 |
| 1.0987 | 36.98 | 13500 | 0.2829 | 0.2619 |
| 1.0873 | 38.36 | 14000 | 0.2864 | 0.2608 |
| 1.0848 | 39.73 | 14500 | 0.2827 | 0.2577 |
| 1.0628 | 41.1 | 15000 | 0.2896 | 0.2581 |
| 1.0815 | 42.47 | 15500 | 0.2814 | 0.2561 |
| 1.0587 | 43.83 | 16000 | 0.2738 | 0.2542 |
| 1.0709 | 45.21 | 16500 | 0.2785 | 0.2578 |
| 1.0512 | 46.57 | 17000 | 0.2793 | 0.2539 |
| 1.0396 | 47.94 | 17500 | 0.2788 | 0.2525 |
| 1.0481 | 49.31 | 18000 | 0.2777 | 0.2534 |
### Evaluation Commands
1. To evaluate on `mozilla-foundation/common_voice_7_0` with split `test`
```bash
python eval.py --model_id patrickvonplaten/xls-r-300m-sv-cv8 --dataset mozilla-foundation/common_voice_8_0 --config sv-SE --split test
```
2. To evaluate on `speech-recognition-community-v2/dev_data`
```bash
python eval.py --model_id patrickvonplaten/xls-r-300m-sv-cv8 --dataset speech-recognition-community-v2/dev_data --config sv --split validation --chunk_length_s 5.0 --stride_length_s 1.0
```
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.1+cu113
- Datasets 1.18.4.dev0
- Tokenizers 0.10.3
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