O0515HMA15H
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: 0.0221
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: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.6733 | 0.09 | 10 | 1.2978 |
| 0.374 | 0.18 | 20 | 0.1601 |
| 0.1499 | 0.27 | 30 | 0.1655 |
| 0.1545 | 0.36 | 40 | 0.1513 |
| 0.1503 | 0.45 | 50 | 0.1519 |
| 0.1499 | 0.54 | 60 | 0.1490 |
| 0.1525 | 0.63 | 70 | 0.1474 |
| 0.1492 | 0.73 | 80 | 0.1559 |
| 0.146 | 0.82 | 90 | 0.1491 |
| 0.1475 | 0.91 | 100 | 0.1481 |
| 0.1495 | 1.0 | 110 | 0.1489 |
| 0.145 | 1.09 | 120 | 0.1474 |
| 0.145 | 1.18 | 130 | 0.1501 |
| 0.1469 | 1.27 | 140 | 0.1489 |
| 0.1486 | 1.36 | 150 | 0.1488 |
| 0.1443 | 1.45 | 160 | 0.1479 |
| 0.1439 | 1.54 | 170 | 0.1437 |
| 0.1311 | 1.63 | 180 | 0.2197 |
| 0.107 | 1.72 | 190 | 0.0720 |
| 0.0667 | 1.81 | 200 | 0.0615 |
| 0.0544 | 1.9 | 210 | 0.0643 |
| 0.0451 | 1.99 | 220 | 0.0503 |
| 0.0489 | 2.08 | 230 | 0.0386 |
| 0.0307 | 2.18 | 240 | 0.0298 |
| 0.0227 | 2.27 | 250 | 0.0274 |
| 0.0293 | 2.36 | 260 | 0.0244 |
| 0.0254 | 2.45 | 270 | 0.0245 |
| 0.0201 | 2.54 | 280 | 0.0243 |
| 0.0269 | 2.63 | 290 | 0.0235 |
| 0.0235 | 2.72 | 300 | 0.0224 |
| 0.0216 | 2.81 | 310 | 0.0220 |
| 0.0242 | 2.9 | 320 | 0.0224 |
| 0.0242 | 2.99 | 330 | 0.0221 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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Base model
allenai/OLMo-1B