|
--- |
|
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 an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6644 |
|
- Accuracy: 0.9596 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- 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: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
| No log | 0.9771 | 32 | 2.2835 | 0.4242 | |
|
| No log | 1.9847 | 65 | 1.8355 | 0.6700 | |
|
| No log | 2.9924 | 98 | 1.4781 | 0.7576 | |
|
| 2.2064 | 4.0 | 131 | 1.1889 | 0.8721 | |
|
| 2.2064 | 4.9771 | 163 | 1.0536 | 0.8687 | |
|
| 2.2064 | 5.9847 | 196 | 0.8963 | 0.8956 | |
|
| 1.3725 | 6.9924 | 229 | 0.7865 | 0.9293 | |
|
| 1.3725 | 8.0 | 262 | 0.7059 | 0.9495 | |
|
| 1.3725 | 8.9771 | 294 | 0.6644 | 0.9596 | |
|
| 0.9706 | 9.7710 | 320 | 0.6516 | 0.9596 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.3 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
