metadata
tags:
- generated_from_trainer
metrics:
- recall
- precision
- f1
model-index:
- name: checkpoint-97-2ep3bsfrmulti2
results: []
checkpoint-97-2ep3bsfrmulti2
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2816
- Recall: 0.9677
- Precision: 0.8108
- F1: 0.8824
- Roc Auc: 0.5206
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: 194
Training results
| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F1 | Roc Auc |
|---|---|---|---|---|---|---|---|
| 0.4534 | 0.5 | 97 | 0.8642 | 1.0 | 0.6458 | 0.7848 | 0.6804 |
| 0.0011 | 1.5 | 194 | 0.2816 | 0.9677 | 0.8108 | 0.8824 | 0.5206 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.2