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---
tags:
- generated_from_trainer
model-index:
- name: completed-model
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)
# completed-model
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3186
- Rewards/chosen: -0.6296
- Rewards/rejected: -2.5591
- Rewards/accuracies: 0.8571
- Rewards/margins: 1.9295
- Logps/rejected: -296.3221
- Logps/chosen: -425.5087
- Logits/rejected: -2.2481
- Logits/chosen: -1.7413
## 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-07
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- distributed_type: multi-GPU
- num_devices: 40
- total_train_batch_size: 120
- total_eval_batch_size: 120
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 18
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4772 | 0.1 | 61 | 0.4037 | -0.3256 | -1.2099 | 0.8095 | 0.8843 | -282.8301 | -422.4691 | -2.1649 | -1.6678 |
| 0.3859 | 0.2 | 122 | 0.3681 | -0.3816 | -1.7445 | 0.7143 | 1.3629 | -288.1762 | -423.0287 | -2.2536 | -1.7385 |
| 0.3061 | 0.3 | 183 | 0.3546 | -0.4969 | -2.1025 | 0.8095 | 1.6056 | -291.7559 | -424.1818 | -2.1989 | -1.7108 |
| 0.3765 | 0.4 | 244 | 0.3374 | -0.5153 | -2.1301 | 0.7619 | 1.6148 | -292.0326 | -424.3660 | -2.2182 | -1.7222 |
| 0.2819 | 0.5 | 305 | 0.3303 | -0.4402 | -2.1809 | 0.8095 | 1.7407 | -292.5404 | -423.6147 | -2.1835 | -1.6998 |
| 0.3009 | 0.6 | 366 | 0.3314 | -0.8026 | -2.7756 | 0.8571 | 1.9730 | -298.4871 | -427.2388 | -2.2430 | -1.7529 |
| 0.3015 | 0.7 | 427 | 0.3228 | -0.6439 | -2.5710 | 0.9048 | 1.9271 | -296.4410 | -425.6519 | -2.2258 | -1.7303 |
| 0.3407 | 0.8 | 488 | 0.3185 | -0.7270 | -2.7118 | 0.8571 | 1.9847 | -297.8488 | -426.4829 | -2.2530 | -1.7496 |
| 0.3149 | 0.9 | 549 | 0.3186 | -0.6296 | -2.5591 | 0.8571 | 1.9295 | -296.3221 | -425.5087 | -2.2481 | -1.7413 |
### Framework versions
- Transformers 4.35.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1
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