metadata
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/conifer
model-index:
- name: rlced_conifer_zephyr-7b-dpo-full
results: []
rlced_conifer_zephyr-7b-dpo-full
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the data/conifer dataset. It achieves the following results on the evaluation set:
- Loss: 0.2006
- Rewards/chosen: -4.0000
- Rewards/rejected: -11.3920
- Rewards/accuracies: 0.8687
- Rewards/margins: 7.3920
- Logps/rejected: -1507.9508
- Logps/chosen: -760.1741
- Logits/rejected: -1.6795
- Logits/chosen: -2.0969
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: 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 |
---|---|---|---|---|---|---|---|---|---|---|---|
0.2558 | 0.2107 | 100 | 0.2515 | -3.3402 | -7.6336 | 0.8363 | 4.2934 | -1132.1079 | -694.1878 | -3.1129 | -3.1245 |
0.2204 | 0.4215 | 200 | 0.2260 | -3.7625 | -9.3814 | 0.8587 | 5.6190 | -1306.8950 | -736.4189 | -2.6948 | -2.7329 |
0.204 | 0.6322 | 300 | 0.2096 | -3.3959 | -9.7494 | 0.8650 | 6.3535 | -1343.6858 | -699.7554 | -2.1723 | -2.4109 |
0.1992 | 0.8430 | 400 | 0.2007 | -4.2176 | -11.7584 | 0.8650 | 7.5408 | -1544.5891 | -781.9304 | -1.6459 | -2.0690 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1