metadata
tags:
- generated_from_trainer
metrics:
- recall
- precision
- f1
model-index:
- name: checkpoint-194-5ep3bsfrmulti3
results: []
checkpoint-194-5ep3bsfrmulti3
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1347
- Recall: 0.9355
- Precision: 0.9355
- F1: 0.9355
- Roc Auc: 0.9702
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: 3
- eval_batch_size: 3
- 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: 291
Training results
| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F1 | Roc Auc |
|---|---|---|---|---|---|---|---|
| 0.2212 | 0.33 | 97 | 1.1492 | 0.4839 | 1.0 | 0.6522 | 0.9092 |
| 0.233 | 1.33 | 194 | 0.3849 | 0.9677 | 0.6977 | 0.8108 | 0.6710 |
| 0.0004 | 2.33 | 291 | 0.1347 | 0.9355 | 0.9355 | 0.9355 | 0.9702 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.2