|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: wav2vec2-base-timit-demo-colab9 |
|
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-timit-demo-colab9 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.1922 |
|
- Wer: 1.0 |
|
|
|
## 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: 8 |
|
- 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: 1000 |
|
- num_epochs: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:---:| |
|
| 5.0683 | 1.42 | 500 | 3.2471 | 1.0 | |
|
| 3.1349 | 2.85 | 1000 | 3.2219 | 1.0 | |
|
| 3.1317 | 4.27 | 1500 | 3.2090 | 1.0 | |
|
| 3.1262 | 5.7 | 2000 | 3.2152 | 1.0 | |
|
| 3.1307 | 7.12 | 2500 | 3.2147 | 1.0 | |
|
| 3.1264 | 8.55 | 3000 | 3.2072 | 1.0 | |
|
| 3.1279 | 9.97 | 3500 | 3.2158 | 1.0 | |
|
| 3.1287 | 11.4 | 4000 | 3.2190 | 1.0 | |
|
| 3.1256 | 12.82 | 4500 | 3.2069 | 1.0 | |
|
| 3.1254 | 14.25 | 5000 | 3.2134 | 1.0 | |
|
| 3.1259 | 15.67 | 5500 | 3.2231 | 1.0 | |
|
| 3.1269 | 17.09 | 6000 | 3.2005 | 1.0 | |
|
| 3.1279 | 18.52 | 6500 | 3.1988 | 1.0 | |
|
| 3.1246 | 19.94 | 7000 | 3.1929 | 1.0 | |
|
| 3.128 | 21.37 | 7500 | 3.1864 | 1.0 | |
|
| 3.1245 | 22.79 | 8000 | 3.1868 | 1.0 | |
|
| 3.1266 | 24.22 | 8500 | 3.1852 | 1.0 | |
|
| 3.1239 | 25.64 | 9000 | 3.1855 | 1.0 | |
|
| 3.125 | 27.07 | 9500 | 3.1917 | 1.0 | |
|
| 3.1233 | 28.49 | 10000 | 3.1929 | 1.0 | |
|
| 3.1229 | 29.91 | 10500 | 3.1922 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.11.3 |
|
- Pytorch 1.11.0+cu113 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.10.3 |
|
|
