|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-xls-r-300m-th-v2 |
|
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-xls-r-300m-th-v2 |
|
|
|
This model is a fine-tuned version of [Botnoi/wav2vec2-xls-r-300m-th-v1](https://huggingface.co/Botnoi/wav2vec2-xls-r-300m-th-v1) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3630 |
|
- Wer: 0.3962 |
|
- Cer: 0.0942 |
|
- Clean Cer: 0.0767 |
|
|
|
## 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: 4.533e-08 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- 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 |
|
- training_steps: 9000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Clean Cer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:| |
|
| 0.3323 | 0.68 | 1000 | 0.3635 | 0.3961 | 0.0942 | 0.0767 | |
|
| 0.3386 | 1.36 | 2000 | 0.3632 | 0.3962 | 0.0943 | 0.0768 | |
|
| 0.3453 | 2.03 | 3000 | 0.3632 | 0.3964 | 0.0943 | 0.0768 | |
|
| 0.3392 | 2.71 | 4000 | 0.3632 | 0.3961 | 0.0943 | 0.0767 | |
|
| 0.3399 | 3.39 | 5000 | 0.3634 | 0.3961 | 0.0942 | 0.0768 | |
|
| 0.347 | 4.07 | 6000 | 0.3632 | 0.3961 | 0.0942 | 0.0767 | |
|
| 0.3414 | 4.74 | 7000 | 0.3631 | 0.3962 | 0.0942 | 0.0767 | |
|
| 0.3378 | 5.42 | 8000 | 0.3631 | 0.3961 | 0.0942 | 0.0767 | |
|
| 0.3421 | 6.1 | 9000 | 0.3630 | 0.3962 | 0.0942 | 0.0767 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0.dev0 |
|
- Pytorch 1.13.0+cu116 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
|
|
