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O0515HMA26H
Litzy619/O0515HMA26H
O0515HMA26H 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 May 16, 2024
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- May 16, 2024
- Updated
- May 16, 2024
- SHA
- 07778aa3
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. -->
O0515HMA26H
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: 0.0207
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 |
|---|---|---|---|
| 3.7553 | 0.09 | 10 | 1.0751 |
| 0.3101 | 0.18 | 20 | 0.1586 |
| 0.1516 | 0.27 | 30 | 0.1574 |
| 0.1536 | 0.36 | 40 | 0.1525 |
| 0.1506 | 0.45 | 50 | 0.1515 |
| 0.1499 | 0.54 | 60 | 0.1484 |
| 0.1508 | 0.63 | 70 | 0.1486 |
| 0.1505 | 0.73 | 80 | 0.1573 |
| 0.1472 | 0.82 | 90 | 0.1478 |
| 0.1473 | 0.91 | 100 | 0.1490 |
| 0.1498 | 1.0 | 110 | 0.1494 |
| 0.1457 | 1.09 | 120 | 0.1477 |
| 0.1455 | 1.18 | 130 | 0.1511 |
| 0.1471 | 1.27 | 140 | 0.1482 |
| 0.1476 | 1.36 | 150 | 0.1463 |
| 0.142 | 1.45 | 160 | 0.1428 |
| 0.1298 | 1.54 | 170 | 0.1287 |
| 0.0892 | 1.63 | 180 | 0.0717 |
| 0.0739 | 1.72 | 190 | 0.0641 |
| 0.0571 | 1.81 | 200 | 0.0708 |
| 0.0645 | 1.9 | 210 | 0.0581 |
| 0.0567 | 1.99 | 220 | 0.0537 |
| 0.0551 | 2.08 | 230 | 0.0505 |
| 0.0462 | 2.18 | 240 | 0.0416 |
| 0.0404 | 2.27 | 250 | 0.0406 |
| 0.0368 | 2.36 | 260 | 0.0332 |
| 0.0311 | 2.45 | 270 | 0.0312 |
| 0.0214 | 2.54 | 280 | 0.0285 |
| 0.0284 | 2.63 | 290 | 0.0257 |
| 0.0234 | 2.72 | 300 | 0.0219 |
| 0.0211 | 2.81 | 310 | 0.0209 |
| 0.0197 | 2.9 | 320 | 0.0208 |
| 0.0236 | 2.99 | 330 | 0.0207 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
- License
- apache-2.0
- Created
- May 16, 2024
- Updated
- May 16, 2024