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---
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- data/zephyr_uf_rlced_conifer_ref
model-index:
- name: zephyr-7b-uf-rlced-conifer-group-dpo-2e-alr-0.01
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. -->
# zephyr-7b-uf-rlced-conifer-group-dpo-2e-alr-0.01
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the data/zephyr_uf_rlced_conifer_ref dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2395
- Rewards/chosen: -2.8511
- Rewards/rejected: -8.5888
- Rewards/accuracies: 0.8778
- Rewards/margins: 5.7377
- Logps/rejected: -1262.6172
- Logps/chosen: -677.5837
- Logits/rejected: 3.8778
- Logits/chosen: 1.9376
- Excess Loss: 0.0374
- Alpha 0 Uf: 0.5116
- Alpha 1 Rlced Conifer: 0.4884
- Rewards/chosen 1 Rlced Conifer: -3.0535
- Rewards/rejected 1 Rlced Conifer: -10.0348
- Rewards/accuracies 1 Rlced Conifer: 0.9097
- Rewards/margins 1 Rlced Conifer: 6.9812
- Logps/rejected 1 Rlced Conifer: -1451.0132
- Logps/chosen 1 Rlced Conifer: -728.9337
- Logits/rejected 1 Rlced Conifer: 3.5676
- Logits/chosen 1 Rlced Conifer: 1.5730
- Task Loss 1 Rlced Conifer: 0.1787
- Task Excess Loss 1 Rlced Conifer: 0.0427
- Rewards/chosen 0 Uf: -2.0820
- Rewards/rejected 0 Uf: -3.4336
- Rewards/accuracies 0 Uf: 0.7633
- Rewards/margins 0 Uf: 1.3516
- Logps/rejected 0 Uf: -584.9677
- Logps/chosen 0 Uf: -497.4562
- Logits/rejected 0 Uf: 5.1753
- Logits/chosen 0 Uf: 3.1000
- Task Loss 0 Uf: 0.5185
- Task Excess Loss 0 Uf: 0.0724
## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Excess Loss | Alpha 0 Uf | Alpha 1 Rlced Conifer | Rewards/chosen 1 Rlced Conifer | Rewards/rejected 1 Rlced Conifer | Rewards/accuracies 1 Rlced Conifer | Rewards/margins 1 Rlced Conifer | Logps/rejected 1 Rlced Conifer | Logps/chosen 1 Rlced Conifer | Logits/rejected 1 Rlced Conifer | Logits/chosen 1 Rlced Conifer | Task Loss 1 Rlced Conifer | Task Excess Loss 1 Rlced Conifer | Rewards/chosen 0 Uf | Rewards/rejected 0 Uf | Rewards/accuracies 0 Uf | Rewards/margins 0 Uf | Logps/rejected 0 Uf | Logps/chosen 0 Uf | Logits/rejected 0 Uf | Logits/chosen 0 Uf | Task Loss 0 Uf | Task Excess Loss 0 Uf |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:-----------:|:----------:|:---------------------:|:------------------------------:|:--------------------------------:|:----------------------------------:|:-------------------------------:|:------------------------------:|:----------------------------:|:-------------------------------:|:-----------------------------:|:-------------------------:|:--------------------------------:|:-------------------:|:---------------------:|:-----------------------:|:--------------------:|:-------------------:|:-----------------:|:--------------------:|:------------------:|:--------------:|:---------------------:|
| 0.1689 | 0.4997 | 360 | 0.2674 | -2.2066 | -5.7976 | 0.8656 | 3.5910 | -983.4942 | -613.1316 | 1.9639 | 0.4895 | 0.0642 | 0.5765 | 0.4235 | -2.3017 | -6.6520 | 0.8965 | 4.3503 | -1112.7397 | -653.7553 | 1.7066 | 0.1879 | 0.2091 | 0.0748 | -1.8461 | -2.7792 | 0.7426 | 0.9330 | -519.5245 | -473.8738 | 3.0556 | 1.4702 | 0.5392 | 0.0891 |
| 0.1413 | 0.9993 | 720 | 0.2485 | -2.0138 | -6.1196 | 0.8741 | 4.1059 | -1015.6987 | -593.8471 | 2.5252 | 1.3345 | 0.0465 | 0.6417 | 0.3583 | -2.0972 | -7.0507 | 0.9047 | 4.9535 | -1152.6036 | -633.2974 | 2.1536 | 1.0120 | 0.1925 | 0.0584 | -1.6822 | -2.7943 | 0.7670 | 1.1121 | -521.0374 | -457.4840 | 4.0168 | 2.3771 | 0.4989 | 0.0595 |
| 0.0671 | 1.4990 | 1080 | 0.2408 | -2.5432 | -7.7524 | 0.8741 | 5.2092 | -1178.9786 | -646.7894 | 3.9871 | 2.3348 | 0.0389 | 0.5284 | 0.4716 | -2.6717 | -8.9931 | 0.9071 | 6.3215 | -1346.8500 | -690.7497 | 3.5948 | 1.9516 | 0.1822 | 0.0462 | -2.0401 | -3.3250 | 0.7500 | 1.2849 | -574.1076 | -493.2740 | 5.5773 | 3.5557 | 0.5197 | 0.0655 |
| 0.0649 | 1.9986 | 1440 | 0.2395 | -2.8511 | -8.5888 | 0.8778 | 5.7377 | -1262.6172 | -677.5837 | 3.8778 | 1.9376 | 0.0374 | 0.5116 | 0.4884 | -3.0535 | -10.0348 | 0.9097 | 6.9812 | -1451.0132 | -728.9337 | 3.5676 | 1.5730 | 0.1787 | 0.0427 | -2.0820 | -3.4336 | 0.7633 | 1.3516 | -584.9677 | -497.4562 | 5.1753 | 3.1000 | 0.5185 | 0.0724 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.0a0+81ea7a4
- Datasets 2.21.0
- Tokenizers 0.19.1
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