|
--- |
|
language: |
|
- hi |
|
license: apache-2.0 |
|
tags: |
|
- automatic-speech-recognition |
|
- mozilla-foundation/common_voice_8_0 |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice |
|
model-index: |
|
- name: xls-r-300m-hi |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# xls-r-300m-hi |
|
|
|
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 - HI dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7522 |
|
- Wer: 1.0091 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- 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: 2000 |
|
- num_epochs: 50.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 5.0417 | 2.59 | 500 | 5.1484 | 1.0 | |
|
| 3.3722 | 5.18 | 1000 | 3.3380 | 1.0001 | |
|
| 1.9752 | 7.77 | 1500 | 1.3910 | 1.0074 | |
|
| 1.5868 | 10.36 | 2000 | 1.0298 | 1.0084 | |
|
| 1.4413 | 12.95 | 2500 | 0.9313 | 1.0175 | |
|
| 1.3296 | 15.54 | 3000 | 0.8966 | 1.0194 | |
|
| 1.2746 | 18.13 | 3500 | 0.8875 | 1.0097 | |
|
| 1.2147 | 20.73 | 4000 | 0.8746 | 1.0089 | |
|
| 1.1774 | 23.32 | 4500 | 0.8383 | 1.0198 | |
|
| 1.129 | 25.91 | 5000 | 0.7848 | 1.0167 | |
|
| 1.0995 | 28.5 | 5500 | 0.7992 | 1.0210 | |
|
| 1.0665 | 31.09 | 6000 | 0.7878 | 1.0107 | |
|
| 1.0321 | 33.68 | 6500 | 0.7653 | 1.0082 | |
|
| 1.0068 | 36.27 | 7000 | 0.7635 | 1.0065 | |
|
| 0.9916 | 38.86 | 7500 | 0.7728 | 1.0090 | |
|
| 0.9735 | 41.45 | 8000 | 0.7688 | 1.0070 | |
|
| 0.9745 | 44.04 | 8500 | 0.7455 | 1.0097 | |
|
| 0.9677 | 46.63 | 9000 | 0.7605 | 1.0099 | |
|
| 0.9313 | 49.22 | 9500 | 0.7527 | 1.0097 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.17.0.dev0 |
|
- Pytorch 1.10.2+cu102 |
|
- Datasets 1.18.2.dev0 |
|
- Tokenizers 0.11.0 |
|
|
