rap_phase2_26march_custom
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
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: 10
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
| 0.1376 |
1.0 |
3968 |
0.1012 |
| 0.0825 |
2.0 |
7936 |
0.0518 |
| 0.9985 |
3.0 |
11904 |
0.0451 |
| 0.0379 |
4.0 |
15872 |
0.0324 |
| 0.0281 |
5.0 |
19840 |
0.0253 |
| 0.0096 |
6.0 |
23808 |
0.0204 |
| 0.0062 |
7.0 |
27776 |
0.0147 |
| 0.0072 |
8.0 |
31744 |
0.0106 |
| 0.0013 |
9.0 |
35712 |
0.0129 |
| 0.0002 |
10.0 |
39680 |
0.0130 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="prajwalJumde/rap_phase2_26march_custom")