zephyr-dpo-timedial / README.md
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---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: alignment-handbook/zephyr-7b-sft-full
datasets:
- EllieS/timedial_dpo
model-index:
- name: zephyr-dpo-timedial
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# zephyr-dpo-timedial
This model is a fine-tuned version of [EllieS/zephyr-sft-timedial](https://huggingface.co/EllieS/zephyr-sft-timedial) on the EllieS/timedial_dpo dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2236
- Rewards/chosen: 0.2987
- Rewards/rejected: -1.0958
- Rewards/accuracies: 1.0
- Rewards/margins: 1.3944
- Logps/rejected: -154.5925
- Logps/chosen: -0.6286
- Logits/rejected: -2.7419
- Logits/chosen: -2.7480
## 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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.3995 | 0.35 | 100 | 0.3705 | 0.2856 | -0.5202 | 1.0 | 0.8058 | -97.0354 | -1.9368 | -2.7815 | -2.7803 |
| 0.2236 | 0.69 | 200 | 0.2236 | 0.2987 | -1.0958 | 1.0 | 1.3944 | -154.5925 | -0.6286 | -2.7419 | -2.7480 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2