---
base_model: ./core-350
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: core-350
  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. -->

# core-350
|    Task     |Version| Metric |Value |   |Stderr|
|-------------|------:|--------|-----:|---|-----:|
|arc_challenge|      0|acc     |0.2048|±  |0.0118|
|             |       |acc_norm|0.2509|±  |0.0127|
|arc_easy     |      0|acc     |0.4247|±  |0.0101|
|             |       |acc_norm|0.3965|±  |0.0100|
|boolq        |      1|acc     |0.5468|±  |0.0087|
|hellaswag    |      0|acc     |0.2844|±  |0.0045|
|             |       |acc_norm|0.3031|±  |0.0046|
|openbookqa   |      0|acc     |0.1560|±  |0.0162|
|             |       |acc_norm|0.2660|±  |0.0198|
|piqa         |      0|acc     |0.5854|±  |0.0115|
|             |       |acc_norm|0.5762|±  |0.0115|
|winogrande   |      0|acc     |0.4909|±  |0.0141|

This model is a fine-tuned version of [./core-350](https://huggingface.co/./core-350) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8128
- Accuracy: 0.8237

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 10.0

### Training results



### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1