---
license: apache-2.0
base_model: pszemraj/mega-small-2048-C1024-simplewiki-MR50-tk_ema32
tags:
- generated_from_trainer
metrics:
- accuracy
datasets:
- pszemraj/simple_wikipedia_LM
- JeanKaddour/minipile
pipeline_tag: fill-mask
---

<!-- 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-small-2048-C1024-MR50-sw_minipile-tk_ema32

This model is a fine-tuned version of [pszemraj/mega-small-2048-C1024-simplewiki-MR50-tk_ema32](https://huggingface.co/pszemraj/mega-small-2048-C1024-simplewiki-MR50-tk_ema32) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7559
- Accuracy: 0.4177

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 3208
- gradient_accumulation_steps: 16
- 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
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.0539        | 0.05  | 100  | 5.0404          | 0.2907   |
| 4.8869        | 0.1   | 200  | 4.6659          | 0.3216   |
| 4.6364        | 0.15  | 300  | 4.4565          | 0.3416   |
| 4.8682        | 0.2   | 400  | 4.3119          | 0.3557   |
| 4.3904        | 0.25  | 500  | 4.2410          | 0.3664   |
| 4.3191        | 0.3   | 600  | 4.1880          | 0.3701   |
| 4.5587        | 0.35  | 700  | 4.0996          | 0.3789   |
| 4.1517        | 0.4   | 800  | 4.0724          | 0.3839   |
| 4.1427        | 0.45  | 900  | 4.0177          | 0.3892   |
| 3.8845        | 0.5   | 1000 | 3.9725          | 0.3928   |
| 4.1478        | 0.55  | 1100 | 3.9080          | 0.4007   |
| 4.0271        | 0.6   | 1200 | 3.8979          | 0.4002   |
| 4.0132        | 0.65  | 1300 | 3.8647          | 0.4057   |
| 3.7284        | 0.7   | 1400 | 3.8518          | 0.4063   |
| 3.9346        | 0.75  | 1500 | 3.8178          | 0.4100   |
| 4.0403        | 0.8   | 1600 | 3.8015          | 0.4126   |
| 3.9726        | 0.85  | 1700 | 3.7916          | 0.4138   |
| 3.8489        | 0.9   | 1800 | 3.7630          | 0.4162   |
| 3.7117        | 0.95  | 1900 | 3.7745          | 0.4162   |
| 3.654         | 1.0   | 2000 | 3.7559          | 0.4177   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.1.0.dev20230809+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3