|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice |
|
model-index: |
|
- name: wav2vec2-large-xls-r-300m-hindi |
|
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. --> |
|
|
|
# wav2vec2-large-xls-r-300m-hindi |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.6718 |
|
- Wer: 0.7103 |
|
|
|
## 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: 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: 500 |
|
- num_epochs: 50 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 5.5682 | 2.72 | 400 | 2.1019 | 0.9188 | |
|
| 0.6506 | 5.44 | 800 | 1.9496 | 0.8048 | |
|
| 0.3249 | 8.16 | 1200 | 1.8901 | 0.7515 | |
|
| 0.222 | 10.88 | 1600 | 1.7736 | 0.7115 | |
|
| 0.171 | 13.6 | 2000 | 2.1061 | 0.7507 | |
|
| 0.1428 | 16.33 | 2400 | 2.2476 | 0.7412 | |
|
| 0.1235 | 19.05 | 2800 | 2.3527 | 0.7554 | |
|
| 0.1076 | 21.77 | 3200 | 2.2145 | 0.7404 | |
|
| 0.0982 | 24.49 | 3600 | 2.3603 | 0.7327 | |
|
| 0.0842 | 27.21 | 4000 | 2.4086 | 0.7465 | |
|
| 0.0732 | 29.93 | 4400 | 2.4182 | 0.7259 | |
|
| 0.0672 | 32.65 | 4800 | 2.5249 | 0.7315 | |
|
| 0.0601 | 35.37 | 5200 | 2.5355 | 0.7207 | |
|
| 0.0534 | 38.09 | 5600 | 2.5170 | 0.7191 | |
|
| 0.0477 | 40.81 | 6000 | 2.6001 | 0.7064 | |
|
| 0.0435 | 43.54 | 6400 | 2.7135 | 0.7142 | |
|
| 0.0374 | 46.26 | 6800 | 2.6552 | 0.7127 | |
|
| 0.0348 | 48.98 | 7200 | 2.6718 | 0.7103 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.16.0.dev0 |
|
- Pytorch 1.10.0+cu113 |
|
- Datasets 1.17.1.dev0 |
|
- Tokenizers 0.10.3 |
|
|
