|
--- |
|
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: |
|
- HuggingFaceH4/ultrafeedback_binarized |
|
model-index: |
|
- name: zephyr-7b-align-scan-2e-07-0.5-linear-2.0 |
|
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-align-scan-2e-07-0.5-linear-2.0 |
|
|
|
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 HuggingFaceH4/ultrafeedback_binarized dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6464 |
|
- Rewards/chosen: 0.4833 |
|
- Rewards/rejected: -0.1353 |
|
- Rewards/accuracies: 0.3710 |
|
- Rewards/margins: 0.6186 |
|
- Logps/rejected: -81.3989 |
|
- Logps/chosen: -73.5245 |
|
- Logits/rejected: -2.5552 |
|
- Logits/chosen: -2.5716 |
|
|
|
## 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-07 |
|
- 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: linear |
|
- 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 | |
|
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
|
| 0.6562 | 0.3484 | 100 | 0.6328 | 0.6802 | 0.3841 | 0.3552 | 0.2961 | -80.3602 | -73.1308 | -2.5405 | -2.5565 | |
|
| 0.6601 | 0.6969 | 200 | 0.6410 | 0.2989 | -0.0897 | 0.3452 | 0.3887 | -81.3078 | -73.8934 | -2.5169 | -2.5332 | |
|
| 0.4195 | 1.0453 | 300 | 0.6371 | 0.6242 | 0.1593 | 0.3532 | 0.4648 | -80.8097 | -73.2429 | -2.5193 | -2.5354 | |
|
| 0.3956 | 1.3937 | 400 | 0.6460 | 0.4324 | -0.1472 | 0.3631 | 0.5796 | -81.4227 | -73.6264 | -2.5378 | -2.5541 | |
|
| 0.3945 | 1.7422 | 500 | 0.6465 | 0.3072 | -0.2969 | 0.3710 | 0.6040 | -81.7221 | -73.8769 | -2.5543 | -2.5709 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|