File size: 4,499 Bytes
473666a 7efed13 f035f13 7efed13 473666a f035f13 473666a f035f13 473666a f035f13 473666a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 |
---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- trl
- orpo
- alignment-handbook
- generated_from_trainer
model-index:
- name: zephyr-7b-sft-full-orpo
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/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/statking/huggingface/runs/ehjj41t1)
# zephyr-7b-sft-full-orpo
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5088
- Rewards/chosen: -0.0404
- Rewards/rejected: -0.0510
- Rewards/accuracies: 0.6290
- Rewards/margins: 0.0106
- Logps/rejected: -1.0202
- Logps/chosen: -0.8085
- Logits/rejected: -2.5337
- Logits/chosen: -2.5634
- Nll Loss: 0.4741
- Log Odds Ratio: -0.6379
- Log Odds Chosen: 0.3305
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 100
- 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 | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 0.5707 | 0.1049 | 100 | 1.1268 | -0.0452 | -0.0539 | 0.6369 | 0.0086 | -1.0774 | -0.9045 | -2.5432 | -2.5811 | 1.0893 | -0.6413 | 0.2601 |
| 0.5663 | 0.2098 | 200 | 0.5741 | -0.0440 | -0.0534 | 0.6270 | 0.0094 | -1.0676 | -0.8799 | -2.5377 | -2.5597 | 0.5352 | -0.6447 | 0.2863 |
| 0.5817 | 0.3146 | 300 | 0.5572 | -0.0440 | -0.0531 | 0.6190 | 0.0091 | -1.0628 | -0.8808 | -2.4499 | -2.4818 | 0.5207 | -0.6503 | 0.2780 |
| 0.5724 | 0.4195 | 400 | 0.5416 | -0.0426 | -0.0515 | 0.625 | 0.0089 | -1.0293 | -0.8510 | -2.4026 | -2.4376 | 0.5060 | -0.6551 | 0.2819 |
| 0.5486 | 0.5244 | 500 | 0.5344 | -0.0425 | -0.0526 | 0.6151 | 0.0101 | -1.0514 | -0.8492 | -2.4373 | -2.4718 | 0.4990 | -0.6439 | 0.3193 |
| 0.5156 | 0.6293 | 600 | 0.5242 | -0.0417 | -0.0514 | 0.6151 | 0.0098 | -1.0285 | -0.8333 | -2.5551 | -2.5811 | 0.4882 | -0.6470 | 0.3056 |
| 0.5297 | 0.7341 | 700 | 0.5191 | -0.0411 | -0.0521 | 0.6310 | 0.0110 | -1.0422 | -0.8215 | -2.4477 | -2.4801 | 0.4838 | -0.6351 | 0.3407 |
| 0.5184 | 0.8390 | 800 | 0.5138 | -0.0409 | -0.0532 | 0.6310 | 0.0123 | -1.0647 | -0.8179 | -2.4575 | -2.4922 | 0.4796 | -0.6304 | 0.3783 |
| 0.5235 | 0.9439 | 900 | 0.5088 | -0.0404 | -0.0510 | 0.6290 | 0.0106 | -1.0202 | -0.8085 | -2.5337 | -2.5634 | 0.4741 | -0.6379 | 0.3305 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|