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mega-ar-small-4096-wikitext-103-raw-v1
pszemraj/mega-ar-small-4096-wikitext-103-raw-v1
mega-ar-small-4096-wikitext-103-raw-v1 is a text generation model from pszemraj. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
This model is a fine-tuned version of pszemraj/random-mega-ar-small-4096 on the EleutherAI/wikitextdocumentlevel dataset (wikitext-103-raw-v1). This model has ~ 65M params.
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At a glance
- Task
- Text Generation
- Library
- transformers
- License
- apache-2.0
- Model type
- mega
- Access
- Public
- Created
- Sep 2, 2023
- Updated
- Dec 29, 2025
- SHA
- 9dc0f2f7
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Base models
Model card
From the Hugging Face model README
mega-ar-small-4096: MWE
mega-ar on wikitext-103-raw-v1 (document level)
This model is a fine-tuned version of pszemraj/random-mega-ar-small-4096 on the EleutherAI/wikitext_document_level dataset (wikitext-103-raw-v1). This model has ~ 65M params.
It achieves the following results on the evaluation set:
- Loss: 4.0338
- Accuracy: 0.3243
Training procedure
This was tuned with bf16, while the authors recommend tuning with fp32. Will try fp32 later.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 4
- eval_batch_size: 1
- seed: 80085
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- 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 |
|---|---|---|---|---|
| 7.3662 | 0.11 | 100 | 7.2782 | 0.0935 |
| 6.3064 | 0.22 | 200 | 6.2066 | 0.1634 |
| 5.8203 | 0.33 | 300 | 5.7299 | 0.1931 |
| 5.55 | 0.44 | 400 | 5.4173 | 0.2117 |
| 5.3194 | 0.55 | 500 | 5.1937 | 0.2278 |
| 5.1678 | 0.66 | 600 | 5.0206 | 0.2406 |
| 5.0375 | 0.77 | 700 | 4.8891 | 0.2508 |
| 4.9194 | 0.88 | 800 | 4.7592 | 0.2605 |
| 4.8272 | 0.99 | 900 | 4.6653 | 0.2681 |
| 4.7571 | 1.1 | 1000 | 4.5817 | 0.2754 |
| 4.6345 | 1.21 | 1100 | 4.5066 | 0.2820 |
| 4.6218 | 1.32 | 1200 | 4.4472 | 0.2867 |
| 4.5585 | 1.43 | 1300 | 4.3827 | 0.2923 |
| 4.5047 | 1.54 | 1400 | 4.3328 | 0.2963 |
| 4.4726 | 1.65 | 1500 | 4.2860 | 0.3002 |
| 4.4094 | 1.76 | 1600 | 4.2452 | 0.3038 |
| 4.3705 | 1.87 | 1700 | 4.2168 | 0.3062 |
| 4.3739 | 1.98 | 1800 | 4.1852 | 0.3095 |
| 4.2836 | 2.09 | 1900 | 4.1599 | 0.3112 |
| 4.302 | 2.2 | 2000 | 4.1307 | 0.3149 |
| 4.2847 | 2.31 | 2100 | 4.1113 | 0.3165 |
| 4.2348 | 2.42 | 2200 | 4.0925 | 0.3184 |
| 4.2837 | 2.53 | 2300 | 4.0743 | 0.3207 |
| 4.2058 | 2.64 | 2400 | 4.0612 | 0.3217 |
| 4.22 | 2.75 | 2500 | 4.0494 | 0.3224 |
| 4.1827 | 2.86 | 2600 | 4.0397 | 0.3237 |
| 4.1967 | 2.97 | 2700 | 4.0338 | 0.3243 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0.dev20230727+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Generation
- Library
- transformers
- Type
- mega
- License
- apache-2.0
- Languages
- en
- Created
- Sep 2, 2023
- Updated
- Dec 29, 2025