---
license: apache-2.0
base_model: pszemraj/random-mega-ar-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: PT-random-mega-ar-large-simple_wikipedia_LM-main-2048
  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. -->

# PT-random-mega-ar-large-simple_wikipedia_LM-main-2048

This model is a fine-tuned version of [pszemraj/random-mega-ar-large](https://huggingface.co/pszemraj/random-mega-ar-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3412
- Accuracy: 0.4360

## 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: 0.0005
- train_batch_size: 1
- eval_batch_size: 1
- seed: 80085
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 7.2245        | 0.11  | 100  | 6.9372          | 0.0711   |
| 6.6575        | 0.22  | 200  | 6.2335          | 0.1853   |
| 5.9406        | 0.34  | 300  | 5.3724          | 0.2635   |
| 5.4452        | 0.45  | 400  | 4.9243          | 0.2940   |
| 5.2524        | 0.56  | 500  | 4.6568          | 0.3172   |
| 4.7862        | 0.67  | 600  | 4.4488          | 0.3347   |
| 4.7132        | 0.79  | 700  | 4.2699          | 0.3481   |
| 4.6601        | 0.9   | 800  | 4.1502          | 0.3582   |
| 4.5067        | 1.01  | 900  | 4.0461          | 0.3681   |
| 4.4465        | 1.12  | 1000 | 3.9488          | 0.3773   |
| 4.4493        | 1.24  | 1100 | 3.8681          | 0.3833   |
| 4.3136        | 1.35  | 1200 | 3.8039          | 0.3897   |
| 4.2978        | 1.46  | 1300 | 3.7373          | 0.3956   |
| 4.0475        | 1.57  | 1400 | 3.6874          | 0.4003   |
| 4.1328        | 1.68  | 1500 | 3.6339          | 0.4061   |
| 4.0758        | 1.8   | 1600 | 3.5866          | 0.4115   |
| 3.8489        | 1.91  | 1700 | 3.5438          | 0.4163   |
| 3.913         | 2.02  | 1800 | 3.5136          | 0.4192   |
| 3.7746        | 2.13  | 1900 | 3.4860          | 0.4226   |
| 3.9547        | 2.25  | 2000 | 3.4505          | 0.4255   |
| 3.9726        | 2.36  | 2100 | 3.4283          | 0.4269   |
| 3.7546        | 2.47  | 2200 | 3.3999          | 0.4298   |
| 3.7442        | 2.58  | 2300 | 3.3820          | 0.4317   |
| 3.6848        | 2.7   | 2400 | 3.3687          | 0.4333   |
| 3.5491        | 2.81  | 2500 | 3.3531          | 0.4349   |
| 3.9563        | 2.92  | 2600 | 3.3412          | 0.4360   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.2.0.dev20230907+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3