metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: EVALutionRelationTrain-4
results: []
EVALutionRelationTrain-4
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6940
- Accuracy: 0.5
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
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: 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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 0.35 | 100 | 0.7110 | 0.5 | 0.0 | 0.0 | 0.0 |
| No log | 0.71 | 200 | 0.7130 | 0.5 | 0.5 | 1.0 | 0.6667 |
| No log | 1.06 | 300 | 0.6943 | 0.5 | 0.0 | 0.0 | 0.0 |
| No log | 1.42 | 400 | 0.6932 | 0.5 | 0.5 | 1.0 | 0.6667 |
| 0.7004 | 1.77 | 500 | 0.6946 | 0.5 | 0.0 | 0.0 | 0.0 |
| 0.7004 | 2.13 | 600 | 0.6999 | 0.5 | 0.0 | 0.0 | 0.0 |
| 0.7004 | 2.48 | 700 | 0.6963 | 0.5 | 0.5 | 1.0 | 0.6667 |
| 0.7004 | 2.84 | 800 | 0.6953 | 0.5 | 0.0 | 0.0 | 0.0 |
| 0.7004 | 3.19 | 900 | 0.6932 | 0.5 | 0.5 | 1.0 | 0.6667 |
| 0.6979 | 3.55 | 1000 | 0.6942 | 0.5 | 0.0 | 0.0 | 0.0 |
| 0.6979 | 3.9 | 1100 | 0.6957 | 0.5 | 0.0 | 0.0 | 0.0 |
| 0.6979 | 4.26 | 1200 | 0.6934 | 0.5 | 0.0 | 0.0 | 0.0 |
| 0.6979 | 4.61 | 1300 | 0.6971 | 0.5 | 0.5 | 1.0 | 0.6667 |
| 0.6979 | 4.96 | 1400 | 0.6940 | 0.5 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1