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---
base_model: castorini/afriteva_v2_base
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: plain_tig
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# plain_tig
This model is a fine-tuned version of [castorini/afriteva_v2_base](https://huggingface.co/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 |