|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: test-model |
|
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. --> |
|
|
|
# test-model |
|
|
|
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: 0.2455 |
|
- Accuracy: 0.9336 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 64 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 100 |
|
- training_steps: 600 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
| 0.9682 | 0.9639 | 60 | 0.8113 | 0.6177 | |
|
| 0.7135 | 1.9277 | 120 | 0.6503 | 0.7425 | |
|
| 0.585 | 2.8916 | 180 | 0.5173 | 0.8149 | |
|
| 0.4603 | 3.8554 | 240 | 0.4556 | 0.8551 | |
|
| 0.3855 | 4.8193 | 300 | 0.2616 | 0.9256 | |
|
| 0.284 | 5.7831 | 360 | 0.3075 | 0.9235 | |
|
| 0.2411 | 6.7470 | 420 | 0.2254 | 0.9376 | |
|
| 0.1818 | 7.7108 | 480 | 0.2609 | 0.9356 | |
|
| 0.1644 | 8.6747 | 540 | 0.2562 | 0.9336 | |
|
| 0.1285 | 9.6386 | 600 | 0.2455 | 0.9336 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|