|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base-960h |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vecvanilla |
|
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. --> |
|
|
|
# wav2vecvanilla |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8028 |
|
- Wer: 0.3041 |
|
|
|
## 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: 16 |
|
- 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: 20 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 1.1729 | 1.69 | 100 | 1.0048 | 0.3681 | |
|
| 1.0722 | 3.39 | 200 | 0.9117 | 0.3511 | |
|
| 0.9994 | 5.08 | 300 | 0.9302 | 0.3436 | |
|
| 0.9576 | 6.78 | 400 | 0.8246 | 0.3320 | |
|
| 0.9826 | 8.47 | 500 | 0.7846 | 0.3343 | |
|
| 0.801 | 10.17 | 600 | 0.8600 | 0.3269 | |
|
| 0.8174 | 11.86 | 700 | 0.7871 | 0.3186 | |
|
| 0.7162 | 13.56 | 800 | 0.8164 | 0.3186 | |
|
| 0.7447 | 15.25 | 900 | 0.8965 | 0.3084 | |
|
| 0.6889 | 16.95 | 1000 | 0.8239 | 0.3057 | |
|
| 0.6739 | 18.64 | 1100 | 0.8028 | 0.3041 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|