|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- audiofolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: wav2vec2-base-finetuned-mednames1 |
|
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-mednames1 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5263 |
|
- Accuracy: 0.9727 |
|
|
|
## 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: 3e-05 |
|
- train_batch_size: 5 |
|
- eval_batch_size: 5 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 20 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.2881 | 1.0 | 22 | 2.2690 | 0.2273 | |
|
| 2.2234 | 2.0 | 44 | 2.1631 | 0.2273 | |
|
| 1.9756 | 3.0 | 66 | 1.9277 | 0.5182 | |
|
| 1.7191 | 4.0 | 88 | 1.6293 | 0.6818 | |
|
| 1.4663 | 5.0 | 110 | 1.3919 | 0.7545 | |
|
| 1.27 | 6.0 | 132 | 1.1689 | 0.8182 | |
|
| 1.1112 | 7.0 | 154 | 1.0144 | 0.8364 | |
|
| 0.9623 | 8.0 | 176 | 0.9137 | 0.8545 | |
|
| 0.8764 | 9.0 | 198 | 0.7901 | 0.8909 | |
|
| 0.7776 | 10.0 | 220 | 0.7229 | 0.8727 | |
|
| 0.7266 | 11.0 | 242 | 0.6335 | 0.9 | |
|
| 0.6379 | 12.0 | 264 | 0.5848 | 0.9636 | |
|
| 0.6121 | 13.0 | 286 | 0.5509 | 0.9273 | |
|
| 0.5732 | 14.0 | 308 | 0.5263 | 0.9727 | |
|
| 0.5579 | 15.0 | 330 | 0.5221 | 0.9727 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.27.2 |
|
- Pytorch 1.11.0+cu102 |
|
- Datasets 2.10.1 |
|
- Tokenizers 0.13.2 |
|
|
