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---
license: apache-2.0
base_model: cerebras/btlm-3b-8k-base
tags:
- generated_from_trainer
model-index:
- name: app/bt_qa-out
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. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# app/bt_qa-out
This model is a fine-tuned version of [cerebras/btlm-3b-8k-base](https://huggingface.co/cerebras/btlm-3b-8k-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7451
## 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: 8.5e-05
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 32
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 2.7377 | 0.0 | 500 | 2.5700 |
| 2.5689 | 0.01 | 1000 | 2.4172 |
| 2.6676 | 0.01 | 1500 | 2.3622 |
| 2.4234 | 0.01 | 2000 | 2.3293 |
| 2.2221 | 0.01 | 2500 | 2.3090 |
| 2.3873 | 0.02 | 3000 | 2.2940 |
| 2.2688 | 0.02 | 3500 | 2.2644 |
| 2.4194 | 0.02 | 4000 | 2.2725 |
| 2.4086 | 0.03 | 4500 | 2.2561 |
| 2.4476 | 0.03 | 5000 | 2.2477 |
| 2.1512 | 0.03 | 5500 | 2.2330 |
| 2.1428 | 0.03 | 6000 | 2.2235 |
| 2.2834 | 0.04 | 6500 | 2.2141 |
| 2.2918 | 0.04 | 7000 | 2.2124 |
| 2.4352 | 0.04 | 7500 | 2.2074 |
| 1.7196 | 0.05 | 8000 | 2.2038 |
| 2.2394 | 0.05 | 8500 | 2.1973 |
| 2.1632 | 0.05 | 9000 | 2.1856 |
| 2.4313 | 0.06 | 9500 | 2.1820 |
| 2.4584 | 0.06 | 10000 | 2.1764 |
| 2.3359 | 0.06 | 10500 | 2.1780 |
| 2.2105 | 0.06 | 11000 | 2.1671 |
| 2.3152 | 0.07 | 11500 | 2.1603 |
| 2.3012 | 0.07 | 12000 | 2.1572 |
| 2.4636 | 0.07 | 12500 | 2.1553 |
| 2.0974 | 0.08 | 13000 | 2.1511 |
| 2.298 | 0.08 | 13500 | 2.1481 |
| 2.3312 | 0.08 | 14000 | 2.1445 |
| 2.5315 | 0.08 | 14500 | 2.1381 |
| 2.1854 | 0.09 | 15000 | 2.1364 |
| 2.3069 | 0.09 | 15500 | 2.1355 |
| 2.0756 | 0.09 | 16000 | 2.1331 |
| 2.0094 | 0.1 | 16500 | 2.1306 |
| 2.2674 | 0.1 | 17000 | 2.1230 |
| 1.8427 | 0.1 | 17500 | 2.1176 |
| 2.2277 | 0.1 | 18000 | 2.1168 |
| 2.1398 | 0.11 | 18500 | 2.1152 |
| 1.9927 | 0.11 | 19000 | 2.1088 |
| 2.0119 | 0.11 | 19500 | 2.1105 |
| 2.5796 | 0.12 | 20000 | 2.1040 |
| 1.3256 | 0.12 | 20500 | 2.0993 |
| 2.2051 | 0.12 | 21000 | 2.0992 |
| 1.628 | 0.13 | 21500 | 2.0944 |
| 2.1926 | 0.13 | 22000 | 2.0927 |
| 1.6482 | 0.13 | 22500 | 2.0873 |
| 2.1122 | 0.13 | 23000 | 2.0830 |
| 1.7405 | 0.14 | 23500 | 2.0828 |
| 2.2685 | 0.14 | 24000 | 2.0784 |
| 2.1062 | 0.14 | 24500 | 2.0766 |
| 2.1308 | 0.15 | 25000 | 2.0714 |
| 1.9122 | 0.15 | 25500 | 2.0719 |
| 2.3549 | 0.15 | 26000 | 2.0643 |
| 2.2159 | 0.15 | 26500 | 2.0655 |
| 1.493 | 0.16 | 27000 | 2.0598 |
| 1.893 | 0.16 | 27500 | 2.0557 |
| 2.1902 | 0.16 | 28000 | 2.0533 |
| 2.2353 | 0.17 | 28500 | 2.0524 |
| 1.8736 | 0.17 | 29000 | 2.0519 |
| 2.0511 | 0.17 | 29500 | 2.0449 |
| 1.2872 | 0.17 | 30000 | 2.0453 |
| 1.6353 | 0.18 | 30500 | 2.0377 |
| 1.992 | 0.18 | 31000 | 2.0419 |
| 2.3586 | 0.18 | 31500 | 2.0353 |
| 1.9453 | 0.19 | 32000 | 2.0330 |
| 2.1322 | 0.19 | 32500 | 2.0305 |
| 2.2887 | 0.19 | 33000 | 2.0253 |
| 2.0268 | 0.2 | 33500 | 2.0267 |
| 1.8397 | 0.2 | 34000 | 2.0207 |
| 2.5165 | 0.2 | 34500 | 2.0202 |
| 1.9142 | 0.2 | 35000 | 2.0139 |
| 1.5993 | 0.21 | 35500 | 2.0179 |
| 2.1691 | 0.21 | 36000 | 2.0102 |
| 2.4948 | 0.21 | 36500 | 2.0089 |
| 1.5422 | 0.22 | 37000 | 2.0039 |
| 1.4566 | 0.22 | 37500 | 2.0014 |
| 1.852 | 0.22 | 38000 | 2.0043 |
| 2.199 | 0.22 | 38500 | 1.9987 |
| 1.4852 | 0.23 | 39000 | 1.9976 |
| 1.3 | 0.23 | 39500 | 1.9936 |
| 2.1237 | 0.23 | 40000 | 1.9917 |
| 1.691 | 0.24 | 40500 | 1.9887 |
| 2.2169 | 0.24 | 41000 | 1.9870 |
| 2.1991 | 0.24 | 41500 | 1.9851 |
| 1.9517 | 0.24 | 42000 | 1.9806 |
| 1.6369 | 0.25 | 42500 | 1.9762 |
| 2.2759 | 0.25 | 43000 | 1.9753 |
| 2.2923 | 0.25 | 43500 | 1.9748 |
| 2.2552 | 0.26 | 44000 | 1.9702 |
| 2.066 | 0.26 | 44500 | 1.9683 |
| 2.2703 | 0.26 | 45000 | 1.9686 |
| 2.3544 | 0.27 | 45500 | 1.9648 |
| 2.255 | 0.27 | 46000 | 1.9635 |
| 1.8732 | 0.27 | 46500 | 1.9639 |
| 2.1203 | 0.27 | 47000 | 1.9590 |
| 2.1314 | 0.28 | 47500 | 1.9573 |
| 1.8511 | 0.28 | 48000 | 1.9533 |
| 2.1471 | 0.28 | 48500 | 1.9514 |
| 1.8417 | 0.29 | 49000 | 1.9509 |
| 2.4485 | 0.29 | 49500 | 1.9502 |
| 2.0708 | 0.29 | 50000 | 1.9455 |
| 1.8272 | 0.29 | 50500 | 1.9416 |
| 1.6232 | 0.3 | 51000 | 1.9380 |
| 1.6785 | 0.3 | 51500 | 1.9358 |
| 1.5734 | 0.3 | 52000 | 1.9313 |
| 1.9737 | 0.31 | 52500 | 1.9301 |
| 1.8393 | 0.31 | 53000 | 1.9295 |
| 1.4789 | 0.31 | 53500 | 1.9281 |
| 2.2062 | 0.31 | 54000 | 1.9273 |
| 2.3501 | 0.32 | 54500 | 1.9236 |
| 2.2756 | 0.32 | 55000 | 1.9218 |
| 2.1001 | 0.32 | 55500 | 1.9215 |
| 2.0342 | 0.33 | 56000 | 1.9179 |
| 1.8066 | 0.33 | 56500 | 1.9143 |
| 1.8322 | 0.33 | 57000 | 1.9137 |
| 2.0926 | 0.34 | 57500 | 1.9106 |
| 2.2106 | 0.34 | 58000 | 1.9083 |
| 2.0666 | 0.34 | 58500 | 1.9055 |
| 2.2082 | 0.34 | 59000 | 1.9026 |
| 2.1768 | 0.35 | 59500 | 1.9007 |
| 1.7091 | 0.35 | 60000 | 1.8967 |
| 1.7585 | 0.35 | 60500 | 1.8946 |
| 1.8968 | 0.36 | 61000 | 1.8936 |
| 2.107 | 0.36 | 61500 | 1.8906 |
| 1.5162 | 0.36 | 62000 | 1.8870 |
| 2.0642 | 0.36 | 62500 | 1.8836 |
| 2.0399 | 0.37 | 63000 | 1.8813 |
| 2.3971 | 0.37 | 63500 | 1.8785 |
| 1.7433 | 0.37 | 64000 | 1.8797 |
| 2.0971 | 0.38 | 64500 | 1.8743 |
| 1.8212 | 0.38 | 65000 | 1.8726 |
| 2.1023 | 0.38 | 65500 | 1.8695 |
| 1.9735 | 0.38 | 66000 | 1.8674 |
| 1.3196 | 0.39 | 66500 | 1.8657 |
| 1.9825 | 0.39 | 67000 | 1.8629 |
| 2.0356 | 0.39 | 67500 | 1.8604 |
| 1.8522 | 0.4 | 68000 | 1.8581 |
| 2.2666 | 0.4 | 68500 | 1.8568 |
| 2.3575 | 0.4 | 69000 | 1.8538 |
| 2.0086 | 0.41 | 69500 | 1.8537 |
| 1.9811 | 0.41 | 70000 | 1.8512 |
| 2.0702 | 0.41 | 70500 | 1.8485 |
| 1.8554 | 0.41 | 71000 | 1.8456 |
| 0.5356 | 0.42 | 71500 | 1.8437 |
| 1.4742 | 0.42 | 72000 | 1.8413 |
| 2.1901 | 0.42 | 72500 | 1.8420 |
| 1.7868 | 0.43 | 73000 | 1.8383 |
| 1.3144 | 0.43 | 73500 | 1.8371 |
| 2.1158 | 0.43 | 74000 | 1.8347 |
| 2.0779 | 0.43 | 74500 | 1.8331 |
| 1.9756 | 0.44 | 75000 | 1.8323 |
| 2.3395 | 0.44 | 75500 | 1.8309 |
| 1.895 | 0.44 | 76000 | 1.8283 |
| 2.0369 | 0.45 | 76500 | 1.8274 |
| 1.8068 | 0.45 | 77000 | 1.8251 |
| 2.2153 | 0.45 | 77500 | 1.8227 |
| 2.1389 | 0.45 | 78000 | 1.8212 |
| 1.9166 | 0.46 | 78500 | 1.8197 |
| 1.711 | 0.46 | 79000 | 1.8187 |
| 1.9102 | 0.46 | 79500 | 1.8165 |
| 0.8358 | 0.47 | 80000 | 1.8163 |
| 1.7278 | 0.47 | 80500 | 1.8148 |
| 1.601 | 0.47 | 81000 | 1.8126 |
| 1.9794 | 0.48 | 81500 | 1.8107 |
| 1.7323 | 0.48 | 82000 | 1.8095 |
| 2.2911 | 0.48 | 82500 | 1.8090 |
| 1.8962 | 0.48 | 83000 | 1.8065 |
| 2.3055 | 0.49 | 83500 | 1.8052 |
| 1.6899 | 0.49 | 84000 | 1.8037 |
| 1.6409 | 0.49 | 84500 | 1.8031 |
| 1.9116 | 0.5 | 85000 | 1.8011 |
| 0.6875 | 0.5 | 85500 | 1.8003 |
| 2.0829 | 0.5 | 86000 | 1.7983 |
| 1.5716 | 0.5 | 86500 | 1.7981 |
| 2.4537 | 0.51 | 87000 | 1.7961 |
| 1.8236 | 0.51 | 87500 | 1.7942 |
| 1.641 | 0.51 | 88000 | 1.7931 |
| 1.5533 | 0.52 | 88500 | 1.7916 |
| 1.679 | 0.52 | 89000 | 1.7902 |
| 2.1463 | 0.52 | 89500 | 1.7893 |
| 1.5477 | 0.52 | 90000 | 1.7884 |
| 1.2346 | 0.53 | 90500 | 1.7873 |
| 1.3352 | 0.53 | 91000 | 1.7859 |
| 2.1039 | 0.53 | 91500 | 1.7850 |
| 2.0818 | 0.54 | 92000 | 1.7834 |
| 1.3987 | 0.54 | 92500 | 1.7830 |
| 1.4544 | 0.54 | 93000 | 1.7827 |
| 0.4043 | 0.55 | 93500 | 1.7811 |
| 2.0149 | 0.55 | 94000 | 1.7794 |
| 1.9845 | 0.55 | 94500 | 1.7789 |
| 2.1053 | 0.55 | 95000 | 1.7775 |
| 2.1572 | 0.56 | 95500 | 1.7768 |
| 2.0754 | 0.56 | 96000 | 1.7761 |
| 1.7675 | 0.56 | 96500 | 1.7754 |
| 2.0023 | 0.57 | 97000 | 1.7743 |
| 1.2653 | 0.57 | 97500 | 1.7736 |
| 1.5566 | 0.57 | 98000 | 1.7728 |
| 1.9408 | 0.57 | 98500 | 1.7724 |
| 2.0936 | 0.58 | 99000 | 1.7713 |
| 0.5687 | 0.58 | 99500 | 1.7706 |
| 2.2833 | 0.58 | 100000 | 1.7702 |
| 1.6689 | 0.59 | 100500 | 1.7690 |
| 1.5198 | 0.59 | 101000 | 1.7684 |
| 1.6968 | 0.59 | 101500 | 1.7679 |
| 2.2034 | 0.59 | 102000 | 1.7674 |
| 1.7902 | 0.6 | 102500 | 1.7665 |
| 2.0557 | 0.6 | 103000 | 1.7658 |
| 1.8617 | 0.6 | 103500 | 1.7650 |
| 1.8749 | 0.61 | 104000 | 1.7637 |
| 1.7674 | 0.61 | 104500 | 1.7632 |
| 1.4269 | 0.61 | 105000 | 1.7627 |
| 1.989 | 0.62 | 105500 | 1.7621 |
| 2.1026 | 0.62 | 106000 | 1.7615 |
| 2.0304 | 0.62 | 106500 | 1.7609 |
| 1.6286 | 0.62 | 107000 | 1.7603 |
| 0.9544 | 0.63 | 107500 | 1.7599 |
| 1.6421 | 0.63 | 108000 | 1.7588 |
| 1.9841 | 0.63 | 108500 | 1.7586 |
| 1.7453 | 0.64 | 109000 | 1.7581 |
| 1.2119 | 0.64 | 109500 | 1.7575 |
| 2.1092 | 0.64 | 110000 | 1.7568 |
| 2.0849 | 0.64 | 110500 | 1.7564 |
| 1.9162 | 0.65 | 111000 | 1.7562 |
| 1.01 | 0.65 | 111500 | 1.7560 |
| 1.301 | 0.65 | 112000 | 1.7556 |
| 0.315 | 0.66 | 112500 | 1.7552 |
| 1.9964 | 0.66 | 113000 | 1.7548 |
| 2.4035 | 0.66 | 113500 | 1.7544 |
| 1.3559 | 0.66 | 114000 | 1.7542 |
| 2.1874 | 0.67 | 114500 | 1.7538 |
| 1.4373 | 0.67 | 115000 | 1.7534 |
| 0.0639 | 0.67 | 115500 | 1.7529 |
| 1.7667 | 0.68 | 116000 | 1.7526 |
| 1.6204 | 0.68 | 116500 | 1.7524 |
| 1.9859 | 0.68 | 117000 | 1.7521 |
| 0.9717 | 0.69 | 117500 | 1.7516 |
| 1.8844 | 0.69 | 118000 | 1.7514 |
| 1.3336 | 0.69 | 118500 | 1.7509 |
| 1.5781 | 0.69 | 119000 | 1.7506 |
| 1.8449 | 0.7 | 119500 | 1.7505 |
| 1.5305 | 0.7 | 120000 | 1.7503 |
| 2.1904 | 0.7 | 120500 | 1.7500 |
| 2.2285 | 0.71 | 121000 | 1.7496 |
| 1.8097 | 0.71 | 121500 | 1.7494 |
| 2.3631 | 0.71 | 122000 | 1.7493 |
| 2.0893 | 0.71 | 122500 | 1.7491 |
| 2.1201 | 0.72 | 123000 | 1.7489 |
| 1.8334 | 0.72 | 123500 | 1.7488 |
| 2.0222 | 0.72 | 124000 | 1.7486 |
| 1.6339 | 0.73 | 124500 | 1.7484 |
| 1.6754 | 0.73 | 125000 | 1.7482 |
| 1.3973 | 0.73 | 125500 | 1.7480 |
| 2.0594 | 0.73 | 126000 | 1.7479 |
| 1.8674 | 0.74 | 126500 | 1.7478 |
| 2.1948 | 0.74 | 127000 | 1.7476 |
| 1.4148 | 0.74 | 127500 | 1.7475 |
| 1.6734 | 0.75 | 128000 | 1.7473 |
| 2.2787 | 0.75 | 128500 | 1.7472 |
| 1.8999 | 0.75 | 129000 | 1.7471 |
| 1.6945 | 0.76 | 129500 | 1.7470 |
| 2.0165 | 0.76 | 130000 | 1.7469 |
| 2.2232 | 0.76 | 130500 | 1.7468 |
| 1.6201 | 0.76 | 131000 | 1.7466 |
| 2.4878 | 0.77 | 131500 | 1.7465 |
| 1.5317 | 0.77 | 132000 | 1.7465 |
| 1.9361 | 0.77 | 132500 | 1.7464 |
| 1.7127 | 0.78 | 133000 | 1.7463 |
| 1.7045 | 0.78 | 133500 | 1.7462 |
| 2.1827 | 0.78 | 134000 | 1.7461 |
| 2.0534 | 0.78 | 134500 | 1.7461 |
| 2.0808 | 0.79 | 135000 | 1.7460 |
| 1.9572 | 0.79 | 135500 | 1.7459 |
| 1.8762 | 0.79 | 136000 | 1.7459 |
| 1.4686 | 0.8 | 136500 | 1.7458 |
| 1.6241 | 0.8 | 137000 | 1.7458 |
| 1.4219 | 0.8 | 137500 | 1.7457 |
| 2.1605 | 0.8 | 138000 | 1.7457 |
| 2.1298 | 0.81 | 138500 | 1.7456 |
| 1.414 | 0.81 | 139000 | 1.7456 |
| 1.0115 | 0.81 | 139500 | 1.7455 |
| 1.9471 | 0.82 | 140000 | 1.7455 |
| 1.8873 | 0.82 | 140500 | 1.7455 |
| 1.8286 | 0.82 | 141000 | 1.7454 |
| 2.1418 | 0.83 | 141500 | 1.7454 |
| 1.9755 | 0.83 | 142000 | 1.7454 |
| 1.6908 | 0.83 | 142500 | 1.7454 |
| 2.3842 | 0.83 | 143000 | 1.7453 |
| 1.7665 | 0.84 | 143500 | 1.7453 |
| 1.8266 | 0.84 | 144000 | 1.7453 |
| 0.8768 | 0.84 | 144500 | 1.7453 |
| 1.2274 | 0.85 | 145000 | 1.7453 |
| 1.6647 | 0.85 | 145500 | 1.7453 |
| 1.4071 | 0.85 | 146000 | 1.7452 |
| 1.6073 | 0.85 | 146500 | 1.7452 |
| 2.201 | 0.86 | 147000 | 1.7452 |
| 1.5504 | 0.86 | 147500 | 1.7452 |
| 1.4377 | 0.86 | 148000 | 1.7452 |
| 1.4453 | 0.87 | 148500 | 1.7452 |
| 1.6929 | 0.87 | 149000 | 1.7451 |
| 1.7631 | 0.87 | 149500 | 1.7451 |
| 2.0868 | 0.87 | 150000 | 1.7451 |
| 0.6434 | 0.88 | 150500 | 1.7451 |
| 1.4851 | 0.88 | 151000 | 1.7451 |
| 1.5365 | 0.88 | 151500 | 1.7451 |
| 1.8129 | 0.89 | 152000 | 1.7451 |
| 1.1623 | 0.89 | 152500 | 1.7451 |
| 2.0714 | 0.89 | 153000 | 1.7451 |
| 1.9363 | 0.9 | 153500 | 1.7451 |
| 1.6408 | 0.9 | 154000 | 1.7451 |
| 0.618 | 0.9 | 154500 | 1.7451 |
| 1.7957 | 0.9 | 155000 | 1.7451 |
| 2.0056 | 0.91 | 155500 | 1.7451 |
| 1.3893 | 0.91 | 156000 | 1.7451 |
| 2.1426 | 0.91 | 156500 | 1.7451 |
| 1.6766 | 0.92 | 157000 | 1.7451 |
| 1.4206 | 0.92 | 157500 | 1.7451 |
| 1.7285 | 0.92 | 158000 | 1.7451 |
| 1.5779 | 0.92 | 158500 | 1.7451 |
| 1.8675 | 0.93 | 159000 | 1.7451 |
| 2.0217 | 0.93 | 159500 | 1.7451 |
| 0.9516 | 0.93 | 160000 | 1.7451 |
| 2.219 | 0.94 | 160500 | 1.7450 |
| 1.6214 | 0.94 | 161000 | 1.7451 |
| 1.7134 | 0.94 | 161500 | 1.7451 |
| 1.6128 | 0.94 | 162000 | 1.7451 |
| 2.0817 | 0.95 | 162500 | 1.7450 |
| 1.8055 | 0.95 | 163000 | 1.7451 |
| 1.909 | 0.95 | 163500 | 1.7451 |
| 1.7844 | 0.96 | 164000 | 1.7451 |
| 2.0719 | 0.96 | 164500 | 1.7451 |
| 1.8698 | 0.96 | 165000 | 1.7451 |
| 1.6926 | 0.96 | 165500 | 1.7451 |
| 2.2161 | 0.97 | 166000 | 1.7451 |
| 2.1111 | 0.97 | 166500 | 1.7451 |
| 1.8004 | 0.97 | 167000 | 1.7451 |
| 2.2364 | 0.98 | 167500 | 1.7451 |
| 1.6716 | 0.98 | 168000 | 1.7451 |
| 2.1804 | 0.98 | 168500 | 1.7451 |
| 1.2691 | 0.99 | 169000 | 1.7451 |
| 1.8306 | 0.99 | 169500 | 1.7451 |
| 0.5662 | 0.99 | 170000 | 1.7451 |
| 1.6516 | 0.99 | 170500 | 1.7451 |
| 2.0576 | 1.0 | 171000 | 1.7451 |
| 1.3638 | 1.0 | 171500 | 1.7451 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
|