---
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