zephyr-7b-spin-iter1-v0
This model is a fine-tuned version of argilla/zephyr-7b-spin-iter0-v0 on the argilla/10k_prompts_SPIN_iter1_zephyr_top and argilla/10k_prompts_SPIN_iter0_zephyr_top dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0831
- Rewards/real: 1.3037
- Rewards/generated: -5.4434
- Rewards/accuracies: 0.9792
- Rewards/margins: 6.7471
- Logps/generated: -545.0309
- Logps/real: -272.3726
- Logits/generated: -2.6844
- Logits/real: -2.7197
MT-Bench results
| Model | 1st Turn Score | 2nd Turn Score | Average Score |
|---|---|---|---|
| zephyr-7b-sft-full | 6.6625 | 6.0250 | 6.34375 |
| zephyr-7b-spin-iter0-v0 | 6.64375 | 6.1750 | 6.409375 |
| zephyr-7b-spin-iter1-v0 | 6.90625 | 6.3000 | 6.603125 |
| zephyr-7b-spin-iter2-v0 | 7.1375 | 6.3125 | 6.725000 |
| zephyr-7b-spin-iter3-v0 | 7.09375 | 6.4500 | 6.771875 |
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: 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1827 | 0.49 | 25 | 0.1651 | 0.1714 | -3.3650 | 0.9688 | 3.5364 | -524.2469 | -283.6962 | -2.7482 | -2.7944 |
| 0.0462 | 0.97 | 50 | 0.0835 | 1.4823 | -4.4998 | 1.0 | 5.9821 | -535.5947 | -270.5871 | -2.6963 | -2.7356 |
| 0.0047 | 1.46 | 75 | 0.0837 | 1.3725 | -5.2500 | 0.9896 | 6.6225 | -543.0965 | -271.6846 | -2.6847 | -2.7211 |
| 0.0034 | 1.94 | 100 | 0.0831 | 1.3037 | -5.4434 | 0.9792 | 6.7471 | -545.0309 | -272.3726 | -2.6844 | -2.7197 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2