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---
license: apache-2.0
base_model: pszemraj/mega-ar-350m-v0.12-napierone_epub
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mega-ar-350m-v0.12-napierone_epub-UltraTextbooks-2.1-fw_mix-vN
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. -->
# mega-ar-350m-v0.12-napierone_epub-UltraTextbooks-2.1-fw_mix-vN
This model is a fine-tuned version of [pszemraj/mega-ar-350m-v0.12-napierone_epub](https://huggingface.co/pszemraj/mega-ar-350m-v0.12-napierone_epub) on the BEE-spoke-data/UltraTextbooks-2.1-fw_mix dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9926
- Accuracy: 0.5885
- Num Input Tokens Seen: 3468165120
## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 80085
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 32
- total_train_batch_size: 96
- total_eval_batch_size: 3
- optimizer: Adam with betas=(0.9,0.985) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Input Tokens Seen |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|
| 2.2374 | 0.0454 | 400 | 2.1871 | 0.5588 | 157286400 |
| 2.143 | 0.0907 | 800 | 2.1336 | 0.5665 | 314572800 |
| 2.1272 | 0.1361 | 1200 | 2.1092 | 0.5698 | 471859200 |
| 2.1243 | 0.1814 | 1600 | 2.0929 | 0.5725 | 629145600 |
| 2.1021 | 0.2268 | 2000 | 2.0794 | 0.5747 | 786432000 |
| 2.0794 | 0.2721 | 2400 | 2.0687 | 0.5762 | 943718400 |
| 2.0843 | 0.3175 | 2800 | 2.0592 | 0.5776 | 1101004800 |
| 2.0571 | 0.3628 | 3200 | 2.0507 | 0.5793 | 1258291200 |
| 2.0841 | 0.4082 | 3600 | 2.0435 | 0.5802 | 1415577600 |
| 2.0484 | 0.4535 | 4000 | 2.0363 | 0.5813 | 1572864000 |
| 2.0199 | 0.4989 | 4400 | 2.0315 | 0.5820 | 1730150400 |
| 2.0361 | 0.5442 | 4800 | 2.0261 | 0.5829 | 1887436800 |
| 2.057 | 0.5896 | 5200 | 2.0207 | 0.5838 | 2044723200 |
| 2.0234 | 0.6349 | 5600 | 2.0163 | 0.5845 | 2202009600 |
| 2.073 | 0.6803 | 6000 | 2.0120 | 0.5850 | 2359296000 |
| 2.058 | 0.7256 | 6400 | 2.0074 | 0.5862 | 2516582400 |
| 2.0253 | 0.7710 | 6800 | 2.0041 | 0.5866 | 2673868800 |
| 1.995 | 0.8163 | 7200 | 2.0010 | 0.5872 | 2831155200 |
| 1.9735 | 0.8617 | 7600 | 1.9987 | 0.5875 | 2988441600 |
| 1.9799 | 0.9070 | 8000 | 1.9960 | 0.5880 | 3145728000 |
| 2.0056 | 0.9524 | 8400 | 1.9942 | 0.5882 | 3303014400 |
| 1.9961 | 0.9977 | 8800 | 1.9926 | 0.5884 | 3460300800 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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