---
license: apache-2.0
base_model: pszemraj/mega-ar-small-4096-NC-simplewiki-v1
tags:
- generated_from_trainer
metrics:
- accuracy
inference:
  parameters:
    max_new_tokens: 96
    do_sample: true
    repetition_penalty: 1.1
    no_repeat_ngram_size: 5
    guidance_scale: 1.02
    eta_cutoff: 0.001
datasets:
- JeanKaddour/minipile
---

<!-- 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. -->

# mega-ar-small-4096-NC-minipile-v1

This model is a fine-tuned version of [pszemraj/mega-ar-small-4096-NC-simplewiki-v1](https://huggingface.co/pszemraj/mega-ar-small-4096-NC-simplewiki-v1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7502
- Accuracy: 0.3650

## 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: 1
- eval_batch_size: 1
- seed: 80085
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.7062        | 0.04  | 200  | 5.5259          | 0.1829   |
| 5.4056        | 0.07  | 400  | 5.1650          | 0.2073   |
| 5.1319        | 0.11  | 600  | 4.9704          | 0.2261   |
| 4.9674        | 0.14  | 800  | 4.8417          | 0.2370   |
| 4.951         | 0.18  | 1000 | 4.7261          | 0.2467   |
| 4.7753        | 0.21  | 1200 | 4.6288          | 0.2554   |
| 4.6721        | 0.25  | 1400 | 4.5260          | 0.2678   |
| 4.6081        | 0.28  | 1600 | 4.4409          | 0.2768   |
| 4.4929        | 0.32  | 1800 | 4.3566          | 0.2857   |
| 4.4345        | 0.35  | 2000 | 4.2812          | 0.2957   |
| 4.3024        | 0.39  | 2200 | 4.2085          | 0.3052   |
| 4.2505        | 0.42  | 2400 | 4.1424          | 0.3151   |
| 4.2294        | 0.46  | 2600 | 4.0859          | 0.3217   |
| 4.2766        | 0.49  | 2800 | 4.0372          | 0.3298   |
| 4.1229        | 0.53  | 3000 | 3.9901          | 0.3357   |
| 4.2007        | 0.56  | 3200 | 3.9538          | 0.3410   |
| 3.9723        | 0.6   | 3400 | 3.9186          | 0.3453   |
| 4.0599        | 0.63  | 3600 | 3.8881          | 0.3487   |
| 4.0351        | 0.67  | 3800 | 3.8650          | 0.3515   |
| 3.9324        | 0.7   | 4000 | 3.8419          | 0.3546   |
| 3.9408        | 0.74  | 4200 | 3.8234          | 0.3564   |
| 3.9499        | 0.77  | 4400 | 3.8091          | 0.3585   |
| 3.9456        | 0.81  | 4600 | 3.7938          | 0.3602   |
| 3.9035        | 0.84  | 4800 | 3.7809          | 0.3618   |
| 3.8709        | 0.88  | 5000 | 3.7712          | 0.3631   |
| 3.8189        | 0.92  | 5200 | 3.7612          | 0.3639   |
| 3.7973        | 0.95  | 5400 | 3.7549          | 0.3646   |
| 3.8952        | 0.99  | 5600 | 3.7502          | 0.3650   |


### Framework versions

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