|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice |
|
model-index: |
|
- name: wav2vec2-base-checkpoint-8 |
|
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-checkpoint-8 |
|
|
|
This model is a fine-tuned version of [jiobiala24/wav2vec2-base-checkpoint-7.1](https://huggingface.co/jiobiala24/wav2vec2-base-checkpoint-7.1) on the common_voice dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9561 |
|
- Wer: 0.3271 |
|
|
|
## 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: 32 |
|
- 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| 0.3117 | 1.59 | 1000 | 0.5514 | 0.3451 | |
|
| 0.2509 | 3.19 | 2000 | 0.5912 | 0.3328 | |
|
| 0.1918 | 4.78 | 3000 | 0.6103 | 0.3346 | |
|
| 0.1612 | 6.38 | 4000 | 0.6469 | 0.3377 | |
|
| 0.1388 | 7.97 | 5000 | 0.6597 | 0.3391 | |
|
| 0.121 | 9.57 | 6000 | 0.6911 | 0.3472 | |
|
| 0.1096 | 11.16 | 7000 | 0.7300 | 0.3457 | |
|
| 0.0959 | 12.76 | 8000 | 0.7660 | 0.3400 | |
|
| 0.0882 | 14.35 | 9000 | 0.8316 | 0.3394 | |
|
| 0.0816 | 15.95 | 10000 | 0.8042 | 0.3357 | |
|
| 0.0739 | 17.54 | 11000 | 0.8087 | 0.3346 | |
|
| 0.0717 | 19.14 | 12000 | 0.8590 | 0.3353 | |
|
| 0.066 | 20.73 | 13000 | 0.8750 | 0.3336 | |
|
| 0.0629 | 22.33 | 14000 | 0.8759 | 0.3333 | |
|
| 0.0568 | 23.92 | 15000 | 0.8963 | 0.3321 | |
|
| 0.0535 | 25.52 | 16000 | 0.9391 | 0.3323 | |
|
| 0.0509 | 27.11 | 17000 | 0.9279 | 0.3296 | |
|
| 0.0498 | 28.71 | 18000 | 0.9561 | 0.3271 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.11.3 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 1.13.3 |
|
- Tokenizers 0.10.3 |
|
|
