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O0503HMA18
Litzy619/O0503HMA18
O0503HMA18 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 14, 2024
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- May 14, 2024
- Updated
- May 14, 2024
- SHA
- 752eb7e2
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. -->
O0503HMA18
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: 0.0045
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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2688 | 0.09 | 10 | 0.1920 |
| 0.1638 | 0.18 | 20 | 0.1538 |
| 0.148 | 0.27 | 30 | 0.1657 |
| 0.1576 | 0.36 | 40 | 0.1586 |
| 0.1551 | 0.45 | 50 | 0.1552 |
| 0.1517 | 0.54 | 60 | 0.1523 |
| 0.1541 | 0.63 | 70 | 0.1506 |
| 0.1626 | 0.73 | 80 | 0.1599 |
| 0.151 | 0.82 | 90 | 0.1644 |
| 0.1533 | 0.91 | 100 | 0.1523 |
| 0.1551 | 1.0 | 110 | 0.1501 |
| 0.4893 | 1.09 | 120 | 3.2799 |
| 2.0114 | 1.18 | 130 | 0.1657 |
| 0.2026 | 1.27 | 140 | 0.1434 |
| 0.1741 | 1.36 | 150 | 0.2084 |
| 0.1372 | 1.45 | 160 | 0.0716 |
| 0.0579 | 1.54 | 170 | 0.0395 |
| 0.0516 | 1.63 | 180 | 0.0318 |
| 0.0327 | 1.72 | 190 | 0.0203 |
| 0.0163 | 1.81 | 200 | 0.0208 |
| 0.0191 | 1.9 | 210 | 0.0124 |
| 0.0103 | 1.99 | 220 | 0.0104 |
| 0.0149 | 2.08 | 230 | 0.0090 |
| 0.0124 | 2.18 | 240 | 0.0066 |
| 0.0106 | 2.27 | 250 | 0.0152 |
| 0.0155 | 2.36 | 260 | 0.0073 |
| 0.0058 | 2.45 | 270 | 0.0067 |
| 0.0038 | 2.54 | 280 | 0.0054 |
| 0.0115 | 2.63 | 290 | 0.0053 |
| 0.0072 | 2.72 | 300 | 0.0045 |
| 0.0065 | 2.81 | 310 | 0.0044 |
| 0.0061 | 2.9 | 320 | 0.0045 |
| 0.0091 | 2.99 | 330 | 0.0045 |
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 14, 2024
- Updated
- May 14, 2024