|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-xls-r-1b |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: wav2vec2-1b-Elderly5 |
|
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. --> |
|
|
|
# wav2vec2-1b-Elderly5 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4667 |
|
- Cer: 12.2650 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 50 |
|
- num_epochs: 3 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Cer | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:| |
|
| 8.8394 | 0.2580 | 200 | 2.3937 | 46.8691 | |
|
| 1.5046 | 0.5160 | 400 | 1.3945 | 30.3689 | |
|
| 1.0724 | 0.7741 | 600 | 1.0383 | 24.7180 | |
|
| 0.8815 | 1.0321 | 800 | 0.9401 | 22.6797 | |
|
| 0.7286 | 1.2901 | 1000 | 0.8012 | 20.3360 | |
|
| 0.6375 | 1.5481 | 1200 | 0.6044 | 15.5016 | |
|
| 0.5906 | 1.8062 | 1400 | 0.5698 | 14.4678 | |
|
| 0.5084 | 2.0642 | 1600 | 0.5267 | 13.5280 | |
|
| 0.4162 | 2.3222 | 1800 | 0.5424 | 13.9274 | |
|
| 0.4088 | 2.5802 | 2000 | 0.4654 | 11.9596 | |
|
| 0.3803 | 2.8383 | 2200 | 0.4667 | 12.2650 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.2 |
|
- Pytorch 2.3.1.post100 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.20.1 |
|
|