|
--- |
|
base_model: facebook/wav2vec2-base |
|
license: apache-2.0 |
|
metrics: |
|
- wer |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: wav2vec2-large-xls-r-vi-colab |
|
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-vi-colab |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 4.5540 |
|
- Wer: 1.0 |
|
- Cer: 1.0 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- 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: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-------:|:----:|:---------------:|:---:|:---:| |
|
| 9.6481 | 2.3864 | 315 | 4.4676 | 1.0 | 1.0 | |
|
| 3.8703 | 4.7727 | 630 | 4.4033 | 1.0 | 1.0 | |
|
| 3.4149 | 7.1591 | 945 | 4.7546 | 1.0 | 1.0 | |
|
| 3.4323 | 9.5455 | 1260 | 4.2532 | 1.0 | 1.0 | |
|
| 3.4127 | 11.9318 | 1575 | 4.6692 | 1.0 | 1.0 | |
|
| 3.4185 | 14.3182 | 1890 | 4.3411 | 1.0 | 1.0 | |
|
| 3.4112 | 16.7045 | 2205 | 4.5614 | 1.0 | 1.0 | |
|
| 3.4074 | 19.0909 | 2520 | 4.3545 | 1.0 | 1.0 | |
|
| 3.4073 | 21.4773 | 2835 | 4.4929 | 1.0 | 1.0 | |
|
| 3.4004 | 23.8636 | 3150 | 4.6089 | 1.0 | 1.0 | |
|
| 3.4099 | 26.25 | 3465 | 4.5189 | 1.0 | 1.0 | |
|
| 3.3972 | 28.6364 | 3780 | 4.5540 | 1.0 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
