| | --- |
| | license: apache-2.0 |
| | base_model: allenai/OLMo-1B |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: O0508V2 |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # O0508V2 |
| |
|
| | This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1459 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 5.1761 | 0.09 | 10 | 3.3017 | |
| | | 1.7101 | 0.18 | 20 | 0.2079 | |
| | | 0.1675 | 0.27 | 30 | 0.1572 | |
| | | 0.1525 | 0.36 | 40 | 0.1620 | |
| | | 0.1506 | 0.45 | 50 | 0.1540 | |
| | | 0.152 | 0.54 | 60 | 0.1542 | |
| | | 0.1542 | 0.63 | 70 | 0.1484 | |
| | | 0.1521 | 0.73 | 80 | 0.1561 | |
| | | 0.1547 | 0.82 | 90 | 0.1471 | |
| | | 0.1498 | 0.91 | 100 | 0.1494 | |
| | | 0.1527 | 1.0 | 110 | 0.1522 | |
| | | 0.1473 | 1.09 | 120 | 0.1486 | |
| | | 0.1469 | 1.18 | 130 | 0.1526 | |
| | | 0.1474 | 1.27 | 140 | 0.1504 | |
| | | 0.149 | 1.36 | 150 | 0.1489 | |
| | | 0.1448 | 1.45 | 160 | 0.1471 | |
| | | 0.1457 | 1.54 | 170 | 0.1470 | |
| | | 0.1471 | 1.63 | 180 | 0.1471 | |
| | | 0.1461 | 1.72 | 190 | 0.1505 | |
| | | 0.1454 | 1.81 | 200 | 0.1540 | |
| | | 0.149 | 1.9 | 210 | 0.1509 | |
| | | 0.1468 | 1.99 | 220 | 0.1496 | |
| | | 0.1474 | 2.08 | 230 | 0.1478 | |
| | | 0.1418 | 2.18 | 240 | 0.1463 | |
| | | 0.1433 | 2.27 | 250 | 0.1476 | |
| | | 0.1449 | 2.36 | 260 | 0.1481 | |
| | | 0.1437 | 2.45 | 270 | 0.1464 | |
| | | 0.1418 | 2.54 | 280 | 0.1467 | |
| | | 0.1422 | 2.63 | 290 | 0.1473 | |
| | | 0.1449 | 2.72 | 300 | 0.1458 | |
| | | 0.1438 | 2.81 | 310 | 0.1457 | |
| | | 0.1445 | 2.9 | 320 | 0.1459 | |
| | | 0.1454 | 2.99 | 330 | 0.1459 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.36.0.dev0 |
| | - Pytorch 2.1.2+cu121 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.14.0 |
| |
|
