llama_1b_step2_batch_grad_v1
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3257
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 40
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.2174 | 0.0341 | 50 | 1.3438 |
| 1.2511 | 0.0682 | 100 | 1.1355 |
| 1.0915 | 0.1022 | 150 | 1.0445 |
| 0.9386 | 0.1363 | 200 | 0.9348 |
| 0.9123 | 0.1704 | 250 | 0.8550 |
| 0.5047 | 0.2045 | 300 | 0.7949 |
| 0.8395 | 0.2386 | 350 | 0.7368 |
| 0.9298 | 0.2727 | 400 | 0.6975 |
| 0.7816 | 0.3067 | 450 | 0.6627 |
| 0.6203 | 0.3408 | 500 | 0.6151 |
| 0.4658 | 0.3749 | 550 | 0.5737 |
| 0.5259 | 0.4090 | 600 | 0.5599 |
| 0.4488 | 0.4431 | 650 | 0.5293 |
| 0.6154 | 0.4772 | 700 | 0.5100 |
| 0.5796 | 0.5112 | 750 | 0.4931 |
| 0.6068 | 0.5453 | 800 | 0.4726 |
| 0.482 | 0.5794 | 850 | 0.4616 |
| 0.2877 | 0.6135 | 900 | 0.4501 |
| 0.34 | 0.6476 | 950 | 0.4360 |
| 0.4047 | 0.6817 | 1000 | 0.4295 |
| 0.4238 | 0.7157 | 1050 | 0.4200 |
| 0.5062 | 0.7498 | 1100 | 0.4041 |
| 0.7784 | 0.7839 | 1150 | 0.3911 |
| 0.2211 | 0.8180 | 1200 | 0.3856 |
| 0.4954 | 0.8521 | 1250 | 0.3777 |
| 0.424 | 0.8862 | 1300 | 0.3710 |
| 0.3539 | 0.9202 | 1350 | 0.3640 |
| 0.27 | 0.9543 | 1400 | 0.3591 |
| 0.4994 | 0.9884 | 1450 | 0.3518 |
| 0.2257 | 1.0225 | 1500 | 0.3614 |
| 0.3277 | 1.0566 | 1550 | 0.3609 |
| 0.2337 | 1.0907 | 1600 | 0.3590 |
| 0.2015 | 1.1247 | 1650 | 0.3522 |
| 0.1872 | 1.1588 | 1700 | 0.3530 |
| 0.168 | 1.1929 | 1750 | 0.3520 |
| 0.2204 | 1.2270 | 1800 | 0.3505 |
| 0.1524 | 1.2611 | 1850 | 0.3477 |
| 0.1608 | 1.2952 | 1900 | 0.3439 |
| 0.2468 | 1.3292 | 1950 | 0.3399 |
| 0.2048 | 1.3633 | 2000 | 0.3396 |
| 0.2225 | 1.3974 | 2050 | 0.3376 |
| 0.2628 | 1.4315 | 2100 | 0.3342 |
| 0.214 | 1.4656 | 2150 | 0.3337 |
| 0.1878 | 1.4997 | 2200 | 0.3298 |
| 0.2482 | 1.5337 | 2250 | 0.3300 |
| 0.2568 | 1.5678 | 2300 | 0.3289 |
| 0.2257 | 1.6019 | 2350 | 0.3299 |
| 0.2225 | 1.6360 | 2400 | 0.3290 |
| 0.1962 | 1.6701 | 2450 | 0.3284 |
| 0.2478 | 1.7042 | 2500 | 0.3269 |
| 0.1841 | 1.7382 | 2550 | 0.3270 |
| 0.215 | 1.7723 | 2600 | 0.3269 |
| 0.1999 | 1.8064 | 2650 | 0.3264 |
| 0.2391 | 1.8405 | 2700 | 0.3261 |
| 0.1559 | 1.8746 | 2750 | 0.3258 |
| 0.1577 | 1.9087 | 2800 | 0.3256 |
| 0.1831 | 1.9427 | 2850 | 0.3256 |
| 0.2495 | 1.9768 | 2900 | 0.3257 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.1.0+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1
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