|
--- |
|
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 |
|
|