|
--- |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- evanarlian/common_voice_11_0_id_filtered |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-xls-r-113m-id |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: evanarlian/common_voice_11_0_id_filtered |
|
type: evanarlian/common_voice_11_0_id_filtered |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.4274974633336408 |
|
--- |
|
|
|
<!-- 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-xls-r-113m-id |
|
|
|
This model is a fine-tuned version of [evanarlian/distil-wav2vec2-xls-r-113m-id](https://huggingface.co/evanarlian/distil-wav2vec2-xls-r-113m-id) on the evanarlian/common_voice_11_0_id_filtered dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4804 |
|
- Wer: 0.4275 |
|
|
|
## 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: 0.0002 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 3 |
|
- total_train_batch_size: 24 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.3 |
|
- num_epochs: 30.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| 3.2694 | 0.92 | 1000 | 2.9168 | 1.0000 | |
|
| 2.2449 | 1.84 | 2000 | 1.5711 | 0.9901 | |
|
| 1.2118 | 2.75 | 3000 | 1.0133 | 0.9261 | |
|
| 0.971 | 3.67 | 4000 | 0.8860 | 0.8743 | |
|
| 0.8472 | 4.59 | 5000 | 0.7562 | 0.8180 | |
|
| 0.7436 | 5.51 | 6000 | 0.6800 | 0.7505 | |
|
| 0.6603 | 6.43 | 7000 | 0.6275 | 0.7023 | |
|
| 0.5961 | 7.35 | 8000 | 0.5913 | 0.6589 | |
|
| 0.5458 | 8.26 | 9000 | 0.5605 | 0.6358 | |
|
| 0.5113 | 9.18 | 10000 | 0.5346 | 0.6039 | |
|
| 0.463 | 10.1 | 11000 | 0.5052 | 0.5689 | |
|
| 0.4326 | 11.02 | 12000 | 0.4880 | 0.5497 | |
|
| 0.3981 | 11.94 | 13000 | 0.4778 | 0.5357 | |
|
| 0.3602 | 12.86 | 14000 | 0.4656 | 0.5198 | |
|
| 0.3501 | 13.77 | 15000 | 0.4510 | 0.5085 | |
|
| 0.3199 | 14.69 | 16000 | 0.4617 | 0.5010 | |
|
| 0.3058 | 15.61 | 17000 | 0.4385 | 0.4880 | |
|
| 0.2844 | 16.53 | 18000 | 0.4638 | 0.4930 | |
|
| 0.2729 | 17.45 | 19000 | 0.4594 | 0.4783 | |
|
| 0.2648 | 18.37 | 20000 | 0.4521 | 0.4703 | |
|
| 0.2515 | 19.28 | 21000 | 0.4727 | 0.4627 | |
|
| 0.2428 | 20.2 | 22000 | 0.4566 | 0.4587 | |
|
| 0.2343 | 21.12 | 23000 | 0.4554 | 0.4545 | |
|
| 0.2228 | 22.04 | 24000 | 0.4670 | 0.4506 | |
|
| 0.2135 | 22.96 | 25000 | 0.4458 | 0.4446 | |
|
| 0.2067 | 23.88 | 26000 | 0.4571 | 0.4402 | |
|
| 0.2065 | 24.79 | 27000 | 0.4680 | 0.4359 | |
|
| 0.1968 | 25.71 | 28000 | 0.4702 | 0.4346 | |
|
| 0.1914 | 26.63 | 29000 | 0.4687 | 0.4320 | |
|
| 0.182 | 27.55 | 30000 | 0.4807 | 0.4332 | |
|
| 0.1771 | 28.47 | 31000 | 0.4824 | 0.4308 | |
|
| 0.1728 | 29.38 | 32000 | 0.4804 | 0.4275 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.12.1 |
|
- Datasets 2.7.1 |
|
- Tokenizers 0.13.1 |
|
|
