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: 0.6642
- Precision: 0.5052
- Recall: 0.4082
- F1: 0.4051
- Accuracy: 0.7670
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 | 49 | 0.7285 | 0.7125 | 0.3284 | 0.2862 | 0.7611 |
| No log | 2.0 | 98 | 0.6789 | 0.6397 | 0.3400 | 0.3098 | 0.7685 |
| No log | 3.0 | 147 | 0.6739 | 0.5247 | 0.3754 | 0.3685 | 0.7672 |
| No log | 4.0 | 196 | 0.6650 | 0.4600 | 0.3984 | 0.3886 | 0.7555 |
| No log | 5.0 | 245 | 0.6642 | 0.5052 | 0.4082 | 0.4051 | 0.7670 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1