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---
language:
- or
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_9_0
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_9_0
metrics:
- wer
model-index:
- name: XLS-R-300M - Odia
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition
dataset:
type: mozilla-foundation/common_voice_9_0
name: Common Voice 9
args: or
metrics:
- type: wer
value: 44.343
name: Test WER
- name: Test CER
type: cer
value: 10.989
---
<!-- 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_9_0 - OR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7886
- Wer: 0.5495
- Cer: 0.1311
## 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: 7.5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3071
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 3.5875 | 66.62 | 400 | 3.4289 | 1.0 | 1.0 |
| 1.4065 | 133.31 | 800 | 0.7243 | 0.6619 | 0.1734 |
| 1.007 | 199.92 | 1200 | 0.6611 | 0.5831 | 0.1457 |
| 0.7984 | 266.62 | 1600 | 0.6387 | 0.5520 | 0.1332 |
| 0.6117 | 333.31 | 2000 | 0.7424 | 0.5682 | 0.1376 |
| 0.4926 | 399.92 | 2400 | 0.7627 | 0.5514 | 0.1314 |
| 0.416 | 466.62 | 2800 | 0.7816 | 0.5604 | 0.1320 |
### Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.1.1.dev0
- Tokenizers 0.12.1
|