metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BLESSRelationTrain-2
results: []
BLESSRelationTrain-2
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6280
- Accuracy: 0.8473
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 |
|---|---|---|---|---|
| No log | 0.8 | 100 | 0.6965 | 0.5 |
| No log | 1.6 | 200 | 0.6828 | 0.5868 |
| No log | 2.4 | 300 | 0.7161 | 0.5 |
| No log | 3.2 | 400 | 0.6493 | 0.6377 |
| 0.6926 | 4.0 | 500 | 0.6856 | 0.5269 |
| 0.6926 | 4.8 | 600 | 0.6096 | 0.7784 |
| 0.6926 | 5.6 | 700 | 0.6265 | 0.8204 |
| 0.6926 | 6.4 | 800 | 0.8188 | 0.8054 |
| 0.6926 | 7.2 | 900 | 0.5995 | 0.8503 |
| 0.3811 | 8.0 | 1000 | 0.6280 | 0.8473 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1