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---
language:
- kmr
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- kmr
- model_for_talk
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Kurmanji Kurdish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: kmr
metrics:
- name: Test WER
type: wer
value: 102.308
- name: Test CER
type: cer
value: 538.748
---
<!-- 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-kurdish
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 - KMR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2548
- Wer: 0.2688
## 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: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.3161 | 12.27 | 2000 | 0.4199 | 0.4797 |
| 1.0643 | 24.54 | 4000 | 0.2982 | 0.3721 |
| 0.9718 | 36.81 | 6000 | 0.2762 | 0.3333 |
| 0.8772 | 49.08 | 8000 | 0.2586 | 0.3051 |
| 0.8236 | 61.35 | 10000 | 0.2575 | 0.2865 |
| 0.7745 | 73.62 | 12000 | 0.2603 | 0.2816 |
| 0.7297 | 85.89 | 14000 | 0.2539 | 0.2727 |
| 0.7079 | 98.16 | 16000 | 0.2554 | 0.2681 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
|