|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
- bem |
|
- robust-speech-event |
|
base_model: facebook/wav2vec2-xls-r-300m |
|
model-index: |
|
- name: wav2vec2-large-xls-r-300m-bemba-fds |
|
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-300m-bemba-fds |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the [BembaSpeech](https://github.com/csikasote/BembaSpeech) dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3594 |
|
- Wer: 0.3838 |
|
|
|
## 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: 0.0003 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- 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: 500 |
|
- num_epochs: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 2.9961 | 0.67 | 500 | 0.5157 | 0.7133 | |
|
| 0.5903 | 1.34 | 1000 | 0.3663 | 0.4989 | |
|
| 0.4804 | 2.02 | 1500 | 0.3547 | 0.4653 | |
|
| 0.4146 | 2.69 | 2000 | 0.3274 | 0.4345 | |
|
| 0.3792 | 3.36 | 2500 | 0.3586 | 0.4640 | |
|
| 0.3509 | 4.03 | 3000 | 0.3360 | 0.4316 | |
|
| 0.3114 | 4.7 | 3500 | 0.3382 | 0.4303 | |
|
| 0.2935 | 5.38 | 4000 | 0.3263 | 0.4091 | |
|
| 0.2723 | 6.05 | 4500 | 0.3348 | 0.4175 | |
|
| 0.2502 | 6.72 | 5000 | 0.3317 | 0.4147 | |
|
| 0.2334 | 7.39 | 5500 | 0.3542 | 0.4030 | |
|
| 0.2287 | 8.06 | 6000 | 0.3594 | 0.4067 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.11.3 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 1.13.3 |
|
- Tokenizers 0.10.3 |
|
|
