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---
language:
- km
license: apache-2.0
tags:
- automatic-speech-recognition
- openslr
- robust-speech-event
- km
- generated_from_trainer
model-index:
- name: xls-r-300m-km
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: OpenSLR km
type: openslr
args: km
metrics:
- name: Test WER
type: wer
value: 29.26
- name: Test CER
type: cer
value: 7.93
---
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the openslr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3142
- Wer: 0.3512
# Evaluation results on OpenSLR "evaluation" (self-split) (Running ./eval.py):
- WER: 0.2925882809468374
- CER: 0.0792776460744666
## 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: 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: 100
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.2049 | 4.93 | 400 | 4.5570 | 1.0 |
| 3.569 | 9.87 | 800 | 3.5415 | 1.0 |
| 3.483 | 14.81 | 1200 | 3.3956 | 1.0 |
| 2.1906 | 19.75 | 1600 | 1.1732 | 0.7897 |
| 1.7968 | 24.69 | 2000 | 0.7634 | 0.6678 |
| 1.615 | 29.62 | 2400 | 0.6182 | 0.5922 |
| 1.52 | 34.56 | 2800 | 0.5473 | 0.5479 |
| 1.4696 | 39.5 | 3200 | 0.5002 | 0.5130 |
| 1.4175 | 44.44 | 3600 | 0.4752 | 0.5021 |
| 1.3943 | 49.38 | 4000 | 0.4638 | 0.4944 |
| Pause and Resume | | | | |
| 1.3829 | 4.93 | 400 | 0.4290 | 0.4796 |
| 1.3156 | 9.87 | 800 | 0.3856 | 0.4474 |
| 1.2396 | 14.81 | 1200 | 0.3600 | 0.4307 |
| 1.1444 | 19.75 | 1600 | 0.3423 | 0.4179 |
| 1.0979 | 24.69 | 2000 | 0.3370 | 0.3884 |
| 1.0714 | 29.62 | 2400 | 0.3237 | 0.3710 |
| 1.0442 | 34.56 | 2800 | 0.3336 | 0.3683 |
| 1.0492 | 39.5 | 3200 | 0.3166 | 0.3527 |
| 1.0284 | 44.44 | 3600 | 0.3178 | 0.3566 |
| 1.0302 | 49.38 | 4000 | 0.3142 | 0.3512 |
### 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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