plain_tig
This model is a fine-tuned version of castorini/afriteva_v2_base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3508
- Accuracy: {'accuracy': 0.1460214446952596}
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: 0.0003
- train_batch_size: 64
- eval_batch_size: 16
- 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 |
| 4.8624 |
2.3810 |
100 |
2.5503 |
{'accuracy': 0.11554740406320542} |
| 2.5725 |
4.7619 |
200 |
1.7106 |
{'accuracy': 0.13755643340857787} |
| 1.936 |
7.1429 |
300 |
1.5616 |
{'accuracy': 0.14094243792325056} |
| 1.804 |
9.5238 |
400 |
1.5510 |
{'accuracy': 0.14122460496613995} |
| 1.755 |
11.9048 |
500 |
1.5 |
{'accuracy': 0.14094243792325056} |
| 1.6713 |
14.2857 |
600 |
1.4747 |
{'accuracy': 0.14051918735891647} |
| 1.624 |
16.6667 |
700 |
1.4347 |
{'accuracy': 0.14193002257336343} |
| 1.5757 |
19.0476 |
800 |
1.4028 |
{'accuracy': 0.14432844243792325} |
| 1.5407 |
21.4286 |
900 |
1.3813 |
{'accuracy': 0.14475169300225735} |
| 1.5199 |
23.8095 |
1000 |
1.3686 |
{'accuracy': 0.1451749435665914} |
| 1.4855 |
26.1905 |
1100 |
1.3569 |
{'accuracy': 0.14531602708803612} |
| 1.4744 |
28.5714 |
1200 |
1.3508 |
{'accuracy': 0.1460214446952596} |
Framework versions
- PEFT 0.7.1
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.15.0
- Tokenizers 0.19.1
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("castorini/afriteva_v2_base") model = PeftModel.from_pretrained(base_model, "Hellina/plain_tig")