File size: 1,953 Bytes
ef86cc9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
---
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
|