metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: relatives_psr
results: []
relatives_psr
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0554
- Precision: 0.7125
- Recall: 0.4765
- F1: 0.4668
- Accuracy: 0.9791
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: 2e-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
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 44 | 0.0591 | 0.8332 | 0.4040 | 0.3670 | 0.9764 |
No log | 2.0 | 88 | 0.0541 | 0.7191 | 0.4742 | 0.4308 | 0.9788 |
No log | 3.0 | 132 | 0.0562 | 0.7176 | 0.4238 | 0.4357 | 0.9776 |
No log | 4.0 | 176 | 0.0544 | 0.7158 | 0.4467 | 0.4316 | 0.9794 |
No log | 5.0 | 220 | 0.0554 | 0.7125 | 0.4765 | 0.4668 | 0.9791 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1