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O0428HMA25
Litzy619/O0428HMA25
O0428HMA25 is a machine learning model from Litzy619. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Apr 30, 2024
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Apr 30, 2024
- Updated
- Apr 30, 2024
- SHA
- 2b9e7b37
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
O0428HMA25
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0179
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 80
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3732 | 0.09 | 10 | 0.1777 |
| 0.1625 | 0.18 | 20 | 0.1554 |
| 0.1492 | 0.27 | 30 | 0.1655 |
| 0.1576 | 0.36 | 40 | 0.1524 |
| 0.1518 | 0.45 | 50 | 0.1576 |
| 0.1514 | 0.54 | 60 | 0.1505 |
| 0.1536 | 0.63 | 70 | 0.1484 |
| 0.1497 | 0.73 | 80 | 0.1585 |
| 0.1499 | 0.82 | 90 | 0.1483 |
| 0.1498 | 0.91 | 100 | 0.1500 |
| 0.1518 | 1.0 | 110 | 0.1494 |
| 0.1477 | 1.09 | 120 | 0.1481 |
| 0.1458 | 1.18 | 130 | 0.1525 |
| 0.1472 | 1.27 | 140 | 0.1484 |
| 0.1487 | 1.36 | 150 | 0.1500 |
| 0.1448 | 1.45 | 160 | 0.1456 |
| 0.1363 | 1.54 | 170 | 0.1287 |
| 0.0851 | 1.63 | 180 | 0.0912 |
| 0.152 | 1.72 | 190 | 0.1214 |
| 0.1799 | 1.81 | 200 | 0.0633 |
| 0.0692 | 1.9 | 210 | 0.0533 |
| 0.0482 | 1.99 | 220 | 0.0345 |
| 0.0448 | 2.08 | 230 | 0.0370 |
| 0.0304 | 2.18 | 240 | 0.0237 |
| 0.0484 | 2.27 | 250 | 0.0524 |
| 0.0422 | 2.36 | 260 | 0.0289 |
| 0.0264 | 2.45 | 270 | 0.0223 |
| 0.0174 | 2.54 | 280 | 0.0199 |
| 0.0267 | 2.63 | 290 | 0.0188 |
| 0.0237 | 2.72 | 300 | 0.0185 |
| 0.018 | 2.81 | 310 | 0.0179 |
| 0.0219 | 2.9 | 320 | 0.0180 |
| 0.0228 | 2.99 | 330 | 0.0179 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- apache-2.0
- Created
- Apr 30, 2024
- Updated
- Apr 30, 2024