metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-riddle-finetuned_new
results: []
roberta-base-riddle-finetuned_new
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3741
- Accuracy: 0.8250
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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 12 | 1.3036 | 0.4500 |
No log | 2.0 | 24 | 1.1112 | 0.4750 |
No log | 3.0 | 36 | 1.0265 | 0.4500 |
No log | 4.0 | 48 | 1.1130 | 0.6000 |
No log | 5.0 | 60 | 0.8603 | 0.625 |
No log | 6.0 | 72 | 0.8099 | 0.7750 |
No log | 7.0 | 84 | 0.8668 | 0.7250 |
No log | 8.0 | 96 | 0.7217 | 0.8000 |
No log | 9.0 | 108 | 0.7143 | 0.8250 |
No log | 10.0 | 120 | 0.6371 | 0.8250 |
No log | 11.0 | 132 | 0.6327 | 0.7250 |
No log | 12.0 | 144 | 0.5974 | 0.75 |
No log | 13.0 | 156 | 0.5160 | 0.8000 |
No log | 14.0 | 168 | 0.5336 | 0.75 |
No log | 15.0 | 180 | 0.5201 | 0.8000 |
No log | 16.0 | 192 | 0.4121 | 0.8250 |
No log | 17.0 | 204 | 0.4145 | 0.8000 |
No log | 18.0 | 216 | 0.4475 | 0.875 |
No log | 19.0 | 228 | 0.4147 | 0.8250 |
No log | 20.0 | 240 | 0.3818 | 0.7750 |
No log | 21.0 | 252 | 0.4136 | 0.75 |
No log | 22.0 | 264 | 0.4364 | 0.75 |
No log | 23.0 | 276 | 0.4180 | 0.7250 |
No log | 24.0 | 288 | 0.4145 | 0.75 |
No log | 25.0 | 300 | 0.4141 | 0.8000 |
No log | 26.0 | 312 | 0.3948 | 0.8000 |
No log | 27.0 | 324 | 0.3930 | 0.8250 |
No log | 28.0 | 336 | 0.3851 | 0.8250 |
No log | 29.0 | 348 | 0.3745 | 0.8250 |
No log | 30.0 | 360 | 0.3741 | 0.8250 |
Framework versions
- Transformers 4.37.2
- Pytorch 1.13.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0