Iris Olmo 2 1b Multihop Only K10
This model is a fine-tuned version of allenai/OLMo-2-0425-1B-Instruct on the None dataset. It achieves the following results on the evaluation set: Loss: 1.3327 Model Preparation Time: 0.0118 Soft Mae: 0.1216 Soft...
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 46,0 MB
- Modelo base
- allenai/OLMo-2-0425-1B-Instruct
- Versión
- vRevision 39d7448
- Actualizado
- 20 oct 2026
- Descargas
- 28
- Fuente
- Hugging Face
Descripción de la fuente
iris-olmo-2-1b-multihop-only-k10
This model is a fine-tuned version of allenai/OLMo-2-0425-1B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3327
- Model Preparation Time: 0.0118
- Soft Mae: 0.1216
- Soft Brier: 0.0397
- Student Prelevantmean: 0.2704
- Teacher Prelevantmean: 0.3219
- Bin F1: 0.7910
- Cal Ece: 0.1288
- Cal Brier: 0.1181
- Cal Auroc: 0.9502
- Info Ndcg@p8: 0.9732
- Info Pairwiseacc: 0.7755
- Num Questions: 20
- Num Pairs: 253
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 0.03
- num_epochs: 6.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Soft Mae | Soft Brier | Student Prelevantmean | Teacher Prelevantmean | Bin F1 | Cal Ece | Cal Brier | Cal Auroc | Info Ndcg@p8 | Info Pairwiseacc | Num Questions | Num Pairs |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.4630 | 0.2562 | 38 | 1.6236 | 0.0118 | 0.2745 | 0.1130 | 0.2112 | 0.3219 | 0.0 | 0.1880 | 0.2632 | 0.6501 | 0.7231 | 0.5022 | 20 | 253 |
| 1.4647 | 0.5124 | 76 | 1.4833 | 0.0118 | 0.2780 | 0.0988 | 0.2630 | 0.3219 | 0.0196 | 0.1561 | 0.2406 | 0.7067 | 0.7529 | 0.5412 | 20 | 253 |
| 1.3540 | 0.7686 | 114 | 1.3927 | 0.0118 | 0.2538 | 0.0911 | 0.2544 | 0.3219 | 0.0388 | 0.1448 | 0.2283 | 0.7269 | 0.7593 | 0.5666 | 20 | 253 |
| 1.2624 | 1.0202 | 152 | 1.3260 | 0.0118 | 0.2510 | 0.0822 | 0.3418 | 0.3219 | 0.3636 | 0.0840 | 0.2040 | 0.7505 | 0.8272 | 0.5878 | 20 | 253 |
| 1.0723 | 1.2764 | 190 | 1.2256 | 0.0118 | 0.2164 | 0.0723 | 0.2967 | 0.3219 | 0.4173 | 0.1377 | 0.1898 | 0.8163 | 0.9125 | 0.6550 | 20 | 253 |
| 1.0972 | 1.5327 | 228 | 1.1845 | 0.0118 | 0.1917 | 0.0601 | 0.2804 | 0.3219 | 0.4179 | 0.1355 | 0.1686 | 0.8797 | 0.9242 | 0.6985 | 20 | 253 |
| 0.9822 | 1.7889 | 266 | 1.0331 | 0.0118 | 0.1486 | 0.0422 | 0.2912 | 0.3219 | 0.7101 | 0.1324 | 0.1347 | 0.9256 | 0.9410 | 0.7235 | 20 | 253 |
| 0.8903 | 2.0405 | 304 | 1.1172 | 0.0118 | 0.1448 | 0.0459 | 0.2408 | 0.3219 | 0.6538 | 0.1617 | 0.1415 | 0.9456 | 0.9402 | 0.7424 | 20 | 253 |
| 0.7215 | 2.2967 | 342 | 1.0172 | 0.0118 | 0.1394 | 0.0418 | 0.2594 | 0.3219 | 0.6667 | 0.1463 | 0.1355 | 0.9423 | 0.9605 | 0.7357 | 20 | 253 |
| 0.8471 | 2.5529 | 380 | 1.0209 | 0.0118 | 0.1308 | 0.0369 | 0.3213 | 0.3219 | 0.7692 | 0.1106 | 0.1168 | 0.9377 | 0.9707 | 0.7518 | 20 | 253 |
| 0.6506 | 2.8091 | 418 | 1.0449 | 0.0118 | 0.1329 | 0.0376 | 0.3641 | 0.3219 | 0.8367 | 0.1072 | 0.1015 | 0.9474 | 0.9704 | 0.7633 | 20 | 253 |
| 0.5661 | 3.0607 | 456 | 1.1329 | 0.0118 | 0.1380 | 0.0453 | 0.2453 | 0.3219 | 0.6835 | 0.1539 | 0.1378 | 0.9428 | 0.9620 | 0.7409 | 20 | 253 |
| 0.5664 | 3.3169 | 494 | 1.2448 | 0.0118 | 0.1287 | 0.0446 | 0.2434 | 0.3219 | 0.7284 | 0.1559 | 0.1307 | 0.9502 | 0.9719 | 0.7567 | 20 | 253 |
| 0.5569 | 3.5731 | 532 | 1.1311 | 0.0118 | 0.1285 | 0.0447 | 0.2843 | 0.3219 | 0.7543 | 0.1149 | 0.1194 | 0.9404 | 0.9747 | 0.7591 | 20 | 253 |
| 0.6041 | 3.8293 | 570 | 1.1799 | 0.0118 | 0.1269 | 0.0427 | 0.2981 | 0.3219 | 0.7892 | 0.1011 | 0.1147 | 0.9416 | 0.9740 | 0.7701 | 20 | 253 |
| 0.4112 | 4.0809 | 608 | 1.0701 | 0.0118 | 0.1191 | 0.0356 | 0.2695 | 0.3219 | 0.7195 | 0.1324 | 0.1192 | 0.9550 | 0.9780 | 0.7744 | 20 | 253 |
| 0.3449 | 4.3371 | 646 | 1.2107 | 0.0118 | 0.1223 | 0.0354 | 0.2754 | 0.3219 | 0.7368 | 0.1238 | 0.1199 | 0.9520 | 0.9756 | 0.7677 | 20 | 253 |
| 0.3662 | 4.5933 | 684 | 1.1941 | 0.0118 | 0.1226 | 0.0379 | 0.2682 | 0.3219 | 0.7239 | 0.1396 | 0.1239 | 0.9520 | 0.9756 | 0.7725 | 20 | 253 |
| 0.2984 | 4.8496 | 722 | 1.1552 | 0.0118 | 0.1202 | 0.0409 | 0.2730 | 0.3219 | 0.8045 | 0.1262 | 0.1196 | 0.9470 | 0.9697 | 0.7642 | 20 | 253 |
| 0.2803 | 5.1011 | 760 | 1.2322 | 0.0118 | 0.1206 | 0.0357 | 0.3037 | 0.3219 | 0.8132 | 0.1204 | 0.1146 | 0.9470 | 0.9691 | 0.7575 | 20 | 253 |
| 0.3223 | 5.3574 | 798 | 1.0983 | 0.0118 | 0.1123 | 0.0337 | 0.2953 | 0.3219 | 0.8111 | 0.1083 | 0.1098 | 0.9487 | 0.9692 | 0.7639 | 20 | 253 |
| 0.3059 | 5.6136 | 836 | 1.3210 | 0.0118 | 0.1299 | 0.0456 | 0.2442 | 0.3219 | 0.7081 | 0.1550 | 0.1330 | 0.9460 | 0.9691 | 0.7524 | 20 | 253 |
| 0.3294 | 5.8698 | 874 | 1.2119 | 0.0118 | 0.1231 | 0.0404 | 0.2752 | 0.3219 | 0.7931 | 0.1299 | 0.1204 | 0.9472 | 0.9721 | 0.7777 | 20 | 253 |
| 0.2226 | 6.0 | 894 | 1.3327 | 0.0118 | 0.1216 | 0.0397 | 0.2704 | 0.3219 | 0.7910 | 0.1288 | 0.1181 | 0.9502 | 0.9732 | 0.7755 | 20 | 253 |
Framework versions
- PEFT 0.19.1
- Transformers 5.14.1
- Pytorch 2.5.1+cu124
- Datasets 5.0.0
- Tokenizers 0.22.2
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 20 oct
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Extractos de fuentes
3 extractos--- library_name: peft license: apache-2.0 base_model: allenai/OLMo-2-0425-1B-Instruct tags: - base_model:adapter:allenai/OLMo-2-0425-1B-Instruct - lora - transformers pipeline_tag: text-generation model-index: - name: iris-olmo-2-1b-multihop-only-k10 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. --> # iris-olmo-2-1b-multihop-only-k10 This model is a fine-tuned version of [allenai/OLMo-2-0425-1B-Instruct](https://huggingface.co/allenai/OLMo-2-0425-1B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3327 - Model Preparation Time: 0.0118 - Soft Mae: 0.1216 - Soft Brier: 0.0397 - Student Prelevantmean: 0.2704 - Teacher Prelevantmean: 0.3219 - Bin F1: 0.7910 - Cal Ece: 0.1288 - Cal Brier: 0.1181 - Cal Auroc: 0.9502 - Info Ndcg@p8: 0.9732 - Info Pairwiseacc: 0.7755 - Num Questions: 20 - Num Pairs: 253 ## 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: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 16 - optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: constant - lr_scheduler_warmup_steps: 0.03 - num_epochs: 6.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Soft Mae | Soft Brier | Student Prelevantmean | Teacher Prelevantmean | Bin F1 | Cal Ece | Cal Brier | Cal Auroc | Info Ndcg@p8 | Info Pairwiseacc | Num Questions | Num Pairs | |:-------------:|:------:|:----:|:---------------:|:----------------------:|:--------:|:----------:|:---------------------:|:---------------------:|:------:|:-------:|:---------:|:---------:|:------------:|:----------------:|:-------------:|:---------:| | 1.4630 | 0.2562 | 38 | 1.6236 | 0.0118 | 0.2745 | 0.1130 | 0.2112 | 0.3219 | 0.0 | 0.1880 | 0.2632 | 0.6501 | 0.7231 | 0.5022 | 20 | 253 | | 1.4647 | 0.5124 | 76 | 1.4833 | 0.0118 | 0.2780 | 0.0988 | 0.2630 | 0.3219 | 0.0196 | 0...
Source context: 28 downloads · 0 likes · Pipeline text-generation · Library peft · Repo daryaZare/iris-olmo-2-1b-multihop-only-k10
Source context: 227 downloads · 0 likes · Pipeline text-generation · Library peft · Repo daryaZare/iris-olmo-2-1b-multihop-only-k10
