|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- xtreme_s |
|
metrics: |
|
- wer |
|
base_model: facebook/wav2vec2-large-xlsr-53 |
|
model-index: |
|
- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod6 |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: xtreme_s |
|
type: xtreme_s |
|
config: fleurs.id_id |
|
split: test |
|
args: fleurs.id_id |
|
metrics: |
|
- type: wer |
|
value: 0.5287382128423889 |
|
name: Wer |
|
--- |
|
|
|
<!-- 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-Fleurs-demo-google-colab-Ezra_William_Prod6 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the xtreme_s dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9531 |
|
- Wer: 0.5287 |
|
|
|
## 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: 0.001 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 8 |
|
- 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 |
|
- lr_scheduler_warmup_steps: 600 |
|
- num_epochs: 90 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 5.2079 | 18.18 | 300 | 2.8502 | 1.0 | |
|
| 1.5727 | 36.36 | 600 | 0.8489 | 0.6749 | |
|
| 0.1925 | 54.55 | 900 | 1.0067 | 0.5868 | |
|
| 0.0963 | 72.73 | 1200 | 0.9531 | 0.5287 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.2.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.1 |
|
|
