Text Generation
Transformers
Safetensors
mistral
generated_from_trainer
conversational
Inference Endpoints
text-generation-inference
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zephyr-7b-spin-iter2-v0

This model is a fine-tuned version of argilla/zephyr-7b-spin-iter1-v0 on the argilla/10k_prompts_SPIN_iter2_zephyr_top and the argilla/10k_prompts_SPIN_iter1_zephyr_top dataset.

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

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: 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
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