metadata
license: apache-2.0
base_model: plaguss/zephyr-7b-spin-iter1-v0
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- argilla/10k_prompts_SPIN_iter1_zephyr_top
- argilla/10k_prompts_SPIN_iter2_zephyr_top
model-index:
- name: outputs
results: []
outputs
This model is a fine-tuned version of plaguss/zephyr-7b-spin-iter1-v0 on the argilla/10k_prompts_SPIN_iter1_zephyr_top and the argilla/10k_prompts_SPIN_iter2_zephyr_top datasets. It achieves the following results on the evaluation set:
- Loss: 0.1253
- Rewards/real: -0.5683
- Rewards/generated: -4.9538
- Rewards/accuracies: 0.9479
- Rewards/margins: 4.3854
- Logps/generated: -739.3701
- Logps/real: -278.2851
- Logits/generated: -2.8430
- Logits/real: -2.8375
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: 1e-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: 2.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/real | Rewards/generated | Rewards/accuracies | Rewards/margins | Logps/generated | Logps/real | Logits/generated | Logits/real |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 5.8769 | 0.49 | 25 | 0.1890 | -0.1680 | -2.9833 | 0.9375 | 2.8153 | -719.6649 | -274.2817 | -2.7940 | -2.8382 |
| 0.1202 | 0.97 | 50 | 0.1440 | -0.4164 | -4.2256 | 0.9479 | 3.8092 | -732.0879 | -276.7652 | -2.8395 | -2.8439 |
| 0.0754 | 1.46 | 75 | 0.1298 | -0.5468 | -4.7565 | 0.9583 | 4.2097 | -737.3973 | -278.0700 | -2.8411 | -2.8388 |
| 0.0621 | 1.94 | 100 | 0.1253 | -0.5683 | -4.9538 | 0.9479 | 4.3854 | -739.3701 | -278.2851 | -2.8430 | -2.8375 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2