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---
language:
- sl
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- model_for_talk
- mozilla-foundation/common_voice_8_0
- robust-speech-event
- sl
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: wav2vec2-xls-r-sl-a1
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: sl
metrics:
- name: Test WER
type: wer
value: 0.20626555409164105
- name: Test CER
type: cer
value: 0.051648321634392154
- 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: 0.5406156320830592
- name: Test CER
type: cer
value: 0.22249723590310583
- 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: 55.24
---
<!-- 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 - SL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2756
- Wer: 0.2279
### Evaluation Commands
1. To evaluate on mozilla-foundation/common_voice_8_0 with test split
python eval.py --model_id DrishtiSharma/wav2vec2-xls-r-sl-a1 --dataset mozilla-foundation/common_voice_8_0 --config sl --split test --log_outputs
2. To evaluate on speech-recognition-community-v2/dev_data
python eval.py --model_id DrishtiSharma/wav2vec2-xls-r-sl-a1 --dataset speech-recognition-community-v2/dev_data --config sl --split validation --chunk_length_s 10 --stride_length_s 1
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7.1e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.3881 | 6.1 | 500 | 2.9710 | 1.0 |
| 2.6401 | 12.2 | 1000 | 1.7677 | 0.9734 |
| 1.5152 | 18.29 | 1500 | 0.5564 | 0.6011 |
| 1.2191 | 24.39 | 2000 | 0.4319 | 0.4390 |
| 1.0237 | 30.49 | 2500 | 0.3141 | 0.3175 |
| 0.8892 | 36.59 | 3000 | 0.2748 | 0.2689 |
| 0.8296 | 42.68 | 3500 | 0.2680 | 0.2534 |
| 0.7602 | 48.78 | 4000 | 0.2820 | 0.2506 |
| 0.7186 | 54.88 | 4500 | 0.2672 | 0.2398 |
| 0.6887 | 60.98 | 5000 | 0.2729 | 0.2402 |
| 0.6507 | 67.07 | 5500 | 0.2767 | 0.2361 |
| 0.6226 | 73.17 | 6000 | 0.2817 | 0.2332 |
| 0.6024 | 79.27 | 6500 | 0.2679 | 0.2279 |
| 0.5787 | 85.37 | 7000 | 0.2837 | 0.2316 |
| 0.5744 | 91.46 | 7500 | 0.2838 | 0.2284 |
| 0.5556 | 97.56 | 8000 | 0.2763 | 0.2281 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
|