---
library_name: transformers
license: mit
base_model: KoNqUeRoR3891/HW2-supervised
tags:
- trl
- reward-trainer
- generated_from_trainer
datasets:
- piqa
metrics:
- accuracy
model-index:
- name: HW2-reward
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: piqa
      type: piqa
      config: plain_text
      split: train
      args: plain_text
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.640818858560794
---

<!-- 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. -->

# HW2-reward

This model is a fine-tuned version of [KoNqUeRoR3891/HW2-supervised](https://huggingface.co/KoNqUeRoR3891/HW2-supervised) on the piqa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7024
- Accuracy: 0.6408

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6793        | 1.0   | 3626  | 0.6733          | 0.5782   |
| 0.6767        | 2.0   | 7252  | 0.6590          | 0.6210   |
| 0.5686        | 3.0   | 10878 | 0.7024          | 0.6408   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1