metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: relatives_psr_seq
results: []
relatives_psr_seq
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6376
- Precision: 0.6453
- Recall: 0.2937
- F1: 0.2919
- Accuracy: 0.7824
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 | 0.7001 | 0.6678 | 0.2208 | 0.2122 | 0.7718 |
| No log | 2.0 | 88 | 0.6490 | 0.6596 | 0.2806 | 0.2749 | 0.7818 |
| No log | 3.0 | 132 | 0.6615 | 0.5962 | 0.2484 | 0.2518 | 0.7794 |
| No log | 4.0 | 176 | 0.6732 | 0.5933 | 0.2792 | 0.2793 | 0.7815 |
| No log | 5.0 | 220 | 0.6376 | 0.6453 | 0.2937 | 0.2919 | 0.7824 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1