|
--- |
|
license: apache-2.0 |
|
base_model: facebook/hubert-large-ll60k |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: speech_ocean_hubert_mdd |
|
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. --> |
|
|
|
# speech_ocean_hubert_mdd |
|
|
|
This model is a fine-tuned version of [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.3987 |
|
- Wer: 0.5798 |
|
- Cer: 0.6474 |
|
|
|
## 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: 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: 500 |
|
- num_epochs: 20 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
|
| 94.265 | 0.9873 | 39 | 85.1429 | 0.9995 | 0.9840 | |
|
| 52.6364 | 2.0 | 79 | 32.7798 | 1.0 | 1.0 | |
|
| 27.2435 | 2.9873 | 118 | 14.8924 | 1.0 | 1.0 | |
|
| 10.122 | 4.0 | 158 | 7.1662 | 1.0 | 1.0 | |
|
| 5.6778 | 4.9873 | 197 | 5.3731 | 1.0 | 1.0 | |
|
| 5.3058 | 6.0 | 237 | 5.2800 | 1.0 | 1.0 | |
|
| 5.3233 | 6.9873 | 276 | 5.2647 | 1.0 | 1.0 | |
|
| 5.2846 | 8.0 | 316 | 5.2266 | 1.0 | 1.0 | |
|
| 5.2555 | 8.9873 | 355 | 5.1857 | 1.0 | 1.0 | |
|
| 5.172 | 10.0 | 395 | 5.1649 | 1.0 | 1.0 | |
|
| 5.1551 | 10.9873 | 434 | 5.0741 | 1.0 | 1.0 | |
|
| 5.1312 | 12.0 | 474 | 5.0101 | 1.0 | 1.0 | |
|
| 4.9727 | 12.9873 | 513 | 4.7469 | 1.0 | 1.0 | |
|
| 4.6317 | 14.0 | 553 | 4.3717 | 0.9541 | 0.9580 | |
|
| 4.1657 | 14.9873 | 592 | 3.8313 | 0.8953 | 0.9418 | |
|
| 3.7754 | 16.0 | 632 | 3.3712 | 0.8003 | 0.8418 | |
|
| 3.3744 | 16.9873 | 671 | 2.9940 | 0.7360 | 0.8192 | |
|
| 3.0452 | 18.0 | 711 | 2.6717 | 0.6829 | 0.7675 | |
|
| 2.7951 | 18.9873 | 750 | 2.4711 | 0.6175 | 0.6972 | |
|
| 2.7407 | 19.7468 | 780 | 2.3987 | 0.5798 | 0.6474 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|
