|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: wav2vec2-base-finetuned-ks |
|
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-finetuned-ks |
|
|
|
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: 0.5131 |
|
- Accuracy: 0.8545 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 25 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 8 | 0.6930 | 0.4182 | |
|
| 0.6924 | 2.0 | 16 | 0.6835 | 0.6 | |
|
| 0.6802 | 3.0 | 24 | 0.6618 | 0.6909 | |
|
| 0.649 | 4.0 | 32 | 0.6318 | 0.6364 | |
|
| 0.6306 | 5.0 | 40 | 0.6066 | 0.6545 | |
|
| 0.6306 | 6.0 | 48 | 0.5750 | 0.6545 | |
|
| 0.597 | 7.0 | 56 | 0.5462 | 0.6909 | |
|
| 0.5569 | 8.0 | 64 | 0.5165 | 0.7455 | |
|
| 0.5379 | 9.0 | 72 | 0.4870 | 0.7818 | |
|
| 0.4663 | 10.0 | 80 | 0.4436 | 0.8727 | |
|
| 0.4663 | 11.0 | 88 | 0.4749 | 0.8364 | |
|
| 0.4581 | 12.0 | 96 | 0.3678 | 0.8909 | |
|
| 0.4244 | 13.0 | 104 | 0.4135 | 0.8545 | |
|
| 0.3686 | 14.0 | 112 | 0.3410 | 0.9455 | |
|
| 0.308 | 15.0 | 120 | 0.3530 | 0.8909 | |
|
| 0.308 | 16.0 | 128 | 0.4086 | 0.8364 | |
|
| 0.2677 | 17.0 | 136 | 0.3900 | 0.8545 | |
|
| 0.2419 | 18.0 | 144 | 0.2027 | 0.9455 | |
|
| 0.1973 | 19.0 | 152 | 0.3836 | 0.8727 | |
|
| 0.1483 | 20.0 | 160 | 0.3371 | 0.8909 | |
|
| 0.1483 | 21.0 | 168 | 0.5328 | 0.8 | |
|
| 0.2048 | 22.0 | 176 | 0.3533 | 0.8909 | |
|
| 0.2232 | 23.0 | 184 | 0.4151 | 0.8727 | |
|
| 0.1864 | 24.0 | 192 | 0.2016 | 0.9273 | |
|
| 0.2669 | 25.0 | 200 | 0.5131 | 0.8545 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.29.2 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|
