O0515HMA8H
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: 0.0325
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 |
|---|---|---|---|
| 4.0133 | 0.09 | 10 | 1.8918 |
| 0.6681 | 0.18 | 20 | 0.1609 |
| 0.1558 | 0.27 | 30 | 0.1673 |
| 0.1547 | 0.36 | 40 | 0.1509 |
| 0.1504 | 0.45 | 50 | 0.1505 |
| 0.1508 | 0.54 | 60 | 0.1474 |
| 0.1501 | 0.63 | 70 | 0.1474 |
| 0.1489 | 0.73 | 80 | 0.1567 |
| 0.1468 | 0.82 | 90 | 0.1483 |
| 0.1471 | 0.91 | 100 | 0.1483 |
| 0.1463 | 1.0 | 110 | 0.1367 |
| 0.1333 | 1.09 | 120 | 0.1012 |
| 0.7881 | 1.18 | 130 | 1.9676 |
| 0.3579 | 1.27 | 140 | 0.1056 |
| 0.1074 | 1.36 | 150 | 0.0791 |
| 0.0598 | 1.45 | 160 | 0.0574 |
| 0.0566 | 1.54 | 170 | 0.0557 |
| 0.0596 | 1.63 | 180 | 0.0565 |
| 0.0686 | 1.72 | 190 | 0.0612 |
| 0.0578 | 1.81 | 200 | 0.0551 |
| 0.0572 | 1.9 | 210 | 0.0552 |
| 0.0561 | 1.99 | 220 | 0.0509 |
| 0.0555 | 2.08 | 230 | 0.0517 |
| 0.0484 | 2.18 | 240 | 0.0525 |
| 0.0474 | 2.27 | 250 | 0.0460 |
| 0.0454 | 2.36 | 260 | 0.0370 |
| 0.0386 | 2.45 | 270 | 0.0370 |
| 0.0344 | 2.54 | 280 | 0.0333 |
| 0.0373 | 2.63 | 290 | 0.0350 |
| 0.0345 | 2.72 | 300 | 0.0323 |
| 0.0364 | 2.81 | 310 | 0.0322 |
| 0.0389 | 2.9 | 320 | 0.0325 |
| 0.0361 | 2.99 | 330 | 0.0325 |
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