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---
language:
- ka
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- ka
- robust-speech-event
- model_for_talk
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Georgian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: ka
metrics:
- name: Test WER
type: wer
value: 42.09
- name: Test CER
type: cer
value: 8.01
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: ka
metrics:
- name: Test WER
type: wer
value: 65.32
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: ka
metrics:
- name: Test WER
type: wer
value: 65.03
---
<!-- 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-georgian
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 - KA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3666
- Wer: 0.4211
## 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: 0.0003
- 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: 500
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.8805 | 5.95 | 500 | 0.7547 | 0.8438 |
| 1.2123 | 11.9 | 1000 | 0.4732 | 0.6542 |
| 1.0822 | 17.86 | 1500 | 0.4027 | 0.5778 |
| 0.9938 | 23.81 | 2000 | 0.3847 | 0.5524 |
| 0.9383 | 29.76 | 2500 | 0.3845 | 0.5204 |
| 0.8932 | 35.71 | 3000 | 0.3833 | 0.5297 |
| 0.8495 | 41.67 | 3500 | 0.3759 | 0.5036 |
| 0.8201 | 47.62 | 4000 | 0.3616 | 0.4859 |
| 0.7794 | 53.57 | 4500 | 0.3874 | 0.4938 |
| 0.735 | 59.52 | 5000 | 0.3748 | 0.4782 |
| 0.7082 | 65.48 | 5500 | 0.3615 | 0.4675 |
| 0.669 | 71.43 | 6000 | 0.3797 | 0.4601 |
| 0.6457 | 77.38 | 6500 | 0.3812 | 0.4515 |
| 0.6098 | 83.33 | 7000 | 0.3660 | 0.4343 |
| 0.5874 | 89.29 | 7500 | 0.3640 | 0.4257 |
| 0.5627 | 95.24 | 8000 | 0.3661 | 0.4239 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
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