|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: XLS-R_timit_en |
|
|
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. --> |
|
|
|
|
|
# XLS-R_timit_en |
|
|
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.3799 |
|
|
- Wer: 0.3019 |
|
|
|
|
|
## 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: 1000 |
|
|
- num_epochs: 30 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
|
| 3.5228 | 3.3 | 1000 | 0.9889 | 0.8394 | |
|
|
| 0.6617 | 6.6 | 2000 | 0.3566 | 0.4027 | |
|
|
| 0.3177 | 9.9 | 3000 | 0.3112 | 0.3606 | |
|
|
| 0.2262 | 13.2 | 4000 | 0.3521 | 0.3324 | |
|
|
| 0.1683 | 16.5 | 5000 | 0.3563 | 0.3260 | |
|
|
| 0.137 | 19.8 | 6000 | 0.3605 | 0.3149 | |
|
|
| 0.1139 | 23.1 | 7000 | 0.3768 | 0.3069 | |
|
|
| 0.1068 | 26.4 | 8000 | 0.3643 | 0.3044 | |
|
|
| 0.0897 | 29.7 | 9000 | 0.3799 | 0.3019 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.17.0 |
|
|
- Pytorch 1.12.1+cu113 |
|
|
- Datasets 1.18.3 |
|
|
- Tokenizers 0.13.0 |
|
|
|
