|
|
---
|
|
|
tags:
|
|
|
- generated_from_trainer
|
|
|
metrics:
|
|
|
- accuracy
|
|
|
model-index:
|
|
|
- name: ASD_Behavour-trainining2
|
|
|
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. -->
|
|
|
|
|
|
# ASD_Behavour-trainining2
|
|
|
|
|
|
This model was trained from scratch on an unknown dataset.
|
|
|
It achieves the following results on the evaluation set:
|
|
|
- Loss: 0.9525
|
|
|
- Accuracy: 0.3636
|
|
|
|
|
|
## 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: 8
|
|
|
- eval_batch_size: 8
|
|
|
- seed: 42
|
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
|
|
- lr_scheduler_type: linear
|
|
|
- lr_scheduler_warmup_ratio: 0.1
|
|
|
- training_steps: 30
|
|
|
|
|
|
### Training results
|
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|
|:-------------:|:-------:|:----:|:---------------:|:--------:|
|
|
|
| No log | 0.0667 | 2 | 1.0015 | 0.5556 |
|
|
|
| No log | 1.0667 | 4 | 0.9530 | 0.5556 |
|
|
|
| No log | 2.0667 | 6 | 1.2045 | 0.2222 |
|
|
|
| No log | 3.0667 | 8 | 1.5476 | 0.2593 |
|
|
|
| 0.4992 | 4.0667 | 10 | 1.3886 | 0.2222 |
|
|
|
| 0.4992 | 5.0667 | 12 | 1.1887 | 0.3333 |
|
|
|
| 0.4992 | 6.0667 | 14 | 1.0209 | 0.5185 |
|
|
|
| 0.4992 | 7.0667 | 16 | 0.9728 | 0.7407 |
|
|
|
| 0.4992 | 8.0667 | 18 | 0.9164 | 0.6667 |
|
|
|
| 0.3577 | 9.0667 | 20 | 0.8789 | 0.6667 |
|
|
|
| 0.3577 | 10.0667 | 22 | 0.8177 | 0.6667 |
|
|
|
| 0.3577 | 11.0667 | 24 | 0.8500 | 0.6296 |
|
|
|
| 0.3577 | 12.0667 | 26 | 0.9112 | 0.6296 |
|
|
|
| 0.3577 | 13.0667 | 28 | 0.9497 | 0.6667 |
|
|
|
| 0.1819 | 14.0667 | 30 | 0.9656 | 0.6667 |
|
|
|
|
|
|
|
|
|
### Framework versions
|
|
|
|
|
|
- Transformers 4.41.0
|
|
|
- Pytorch 2.3.0+cu121
|
|
|
- Datasets 2.19.1
|
|
|
- Tokenizers 0.19.1
|
|
|
|
