metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: AV_MAE_2class_DF1M
results: []
AV_MAE_2class_DF1M
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3200
- Accuracy: 0.9335
- F1: 0.9334
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: 28240
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2874 | 0.16 | 4515 | 0.3124 | 0.9181 | 0.9181 |
| 0.4418 | 1.16 | 9030 | 0.3153 | 0.9261 | 0.9260 |
| 0.453 | 2.16 | 13546 | 0.2692 | 0.9305 | 0.9305 |
| 0.2247 | 3.16 | 18062 | 0.2746 | 0.9308 | 0.9307 |
| 0.0751 | 4.16 | 22579 | 0.2604 | 0.9382 | 0.9380 |
| 0.0827 | 5.16 | 27095 | 0.2913 | 0.9366 | 0.9365 |
| 0.1658 | 6.04 | 28240 | 0.3200 | 0.9335 | 0.9334 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.1