|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- superb |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: wav2vec2-base-ks-padpt200 |
|
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-base-ks-padpt200 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.3595 |
|
- Accuracy: 0.5368 |
|
|
|
## 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: 0.003 |
|
- train_batch_size: 256 |
|
- eval_batch_size: 256 |
|
- seed: 0 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 1024 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.2728 | 1.0 | 50 | 1.6540 | 0.6037 | |
|
| 0.8498 | 2.0 | 100 | 1.2559 | 0.6015 | |
|
| 0.7563 | 3.0 | 150 | 1.4192 | 0.5035 | |
|
| 0.701 | 4.0 | 200 | 1.3318 | 0.5641 | |
|
| 0.6592 | 5.0 | 250 | 1.3236 | 0.5666 | |
|
| 0.6404 | 6.0 | 300 | 1.3653 | 0.5469 | |
|
| 0.6315 | 7.0 | 350 | 1.4052 | 0.5082 | |
|
| 0.6306 | 8.0 | 400 | 1.2818 | 0.5590 | |
|
| 0.6297 | 9.0 | 450 | 1.3096 | 0.5659 | |
|
| 0.6056 | 10.0 | 500 | 1.3595 | 0.5368 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.22.0.dev0 |
|
- Pytorch 1.11.0+cu115 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
