File size: 2,408 Bytes
31e9b9e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 |
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SeizureClassifier_Wav2Vec_43243531
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. -->
# SeizureClassifier_Wav2Vec_43243531
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: 0.0063
- Accuracy: 0.9990
## 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: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.13 | 1.0 | 339 | 0.1382 | 0.9616 |
| 0.0931 | 2.0 | 678 | 0.0613 | 0.9839 |
| 0.0265 | 3.0 | 1017 | 0.0248 | 0.9942 |
| 0.026 | 4.0 | 1357 | 0.0612 | 0.9900 |
| 0.0252 | 5.0 | 1696 | 0.0460 | 0.9894 |
| 0.0369 | 6.0 | 2035 | 0.0148 | 0.9968 |
| 0.0018 | 7.0 | 2374 | 0.0049 | 0.9990 |
| 0.0007 | 8.0 | 2714 | 0.0114 | 0.9981 |
| 0.0056 | 9.0 | 3053 | 0.0107 | 0.9987 |
| 0.0003 | 10.0 | 3392 | 0.0067 | 0.9990 |
| 0.0101 | 11.0 | 3731 | 0.0039 | 0.9994 |
| 0.0073 | 12.0 | 4071 | 0.0049 | 0.9994 |
| 0.0113 | 13.0 | 4410 | 0.0061 | 0.9990 |
| 0.0002 | 14.0 | 4749 | 0.0067 | 0.9990 |
| 0.0002 | 14.99 | 5085 | 0.0063 | 0.9990 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
|