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---
language:
- kk
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- kk
- robust-speech-event
- model_for_talk
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: wav2vec2-xls-r-300m-kk-n2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: tt
metrics:
- name: Test WER
type: wer
value: 0.4355
- name: Test CER
type: cer
value: 0.10469915859660263
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: vot
metrics:
- name: Test WER
type: wer
value: NA
- name: Test CER
type: cer
value: NA
---
<!-- 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 - KK dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7149
- Wer: 0.451
### Evaluation Commands
1. To evaluate on mozilla-foundation/common_voice_8_0 with test split
python eval.py --model_id DrishtiSharma/wav2vec2-xls-r-300m-kk-n2 --dataset mozilla-foundation/common_voice_8_0 --config kk --split test --log_outputs
2. To evaluate on speech-recognition-community-v2/dev_data
Kazakh language not found in speech-recognition-community-v2/dev_data!
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.000222
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 1000
- num_epochs: 150.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 9.6799 | 9.09 | 200 | 3.6119 | 1.0 |
| 3.1332 | 18.18 | 400 | 2.5352 | 1.005 |
| 1.0465 | 27.27 | 600 | 0.6169 | 0.682 |
| 0.3452 | 36.36 | 800 | 0.6572 | 0.607 |
| 0.2575 | 45.44 | 1000 | 0.6527 | 0.578 |
| 0.2088 | 54.53 | 1200 | 0.6828 | 0.551 |
| 0.158 | 63.62 | 1400 | 0.7074 | 0.5575 |
| 0.1309 | 72.71 | 1600 | 0.6523 | 0.5595 |
| 0.1074 | 81.8 | 1800 | 0.7262 | 0.5415 |
| 0.087 | 90.89 | 2000 | 0.7199 | 0.521 |
| 0.0711 | 99.98 | 2200 | 0.7113 | 0.523 |
| 0.0601 | 109.09 | 2400 | 0.6863 | 0.496 |
| 0.0451 | 118.18 | 2600 | 0.6998 | 0.483 |
| 0.0378 | 127.27 | 2800 | 0.6971 | 0.4615 |
| 0.0319 | 136.36 | 3000 | 0.7119 | 0.4475 |
| 0.0305 | 145.44 | 3200 | 0.7181 | 0.459 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
|