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---
language:
- sl
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- sl
- robust-speech-event
- model_for_talk
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Slovenian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: sl
metrics:
- name: Test WER
type: wer
value: 18.97
- name: Test CER
type: cer
value: 4.534
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: sl
metrics:
- name: Test WER
type: wer
value: 55.048
- name: Test CER
type: cer
value: 22.739
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: sl
metrics:
- name: Test WER
type: wer
value: 54.81
---
<!-- 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-slovenian
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_7_0 - SL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2093
- Wer: 0.1907
## 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: 7e-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: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.785 | 12.5 | 1000 | 0.7465 | 0.6812 |
| 0.8989 | 25.0 | 2000 | 0.2495 | 0.2732 |
| 0.7118 | 37.5 | 3000 | 0.2126 | 0.2284 |
| 0.6367 | 50.0 | 4000 | 0.2049 | 0.2049 |
| 0.5763 | 62.5 | 5000 | 0.2116 | 0.2055 |
| 0.5196 | 75.0 | 6000 | 0.2111 | 0.1910 |
| 0.4949 | 87.5 | 7000 | 0.2131 | 0.1931 |
| 0.4797 | 100.0 | 8000 | 0.2093 | 0.1907 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
|