metadata
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: Llama-2-7b-spin-rephrased-10k
results: []
Llama-2-7b-spin-rephrased-10k
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1071
- Rewards/real: 10.2171
- Rewards/generated: -7.6243
- Rewards/accuracies: 1.0
- Rewards/margins: 17.8413
- Logps/generated: -358.9117
- Logps/real: -104.6875
- Logits/generated: -0.8781
- Logits/real: -1.4494
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/real | Rewards/generated | Rewards/accuracies | Rewards/margins | Logps/generated | Logps/real | Logits/generated | Logits/real |
---|---|---|---|---|---|---|---|---|---|---|---|
0.1687 | 0.1984 | 62 | 0.1554 | 5.2053 | -5.2548 | 1.0 | 10.4601 | -335.2168 | -154.8048 | -0.7218 | -0.4019 |
0.1204 | 0.3968 | 124 | 0.1153 | 9.3697 | -4.5235 | 1.0 | 13.8932 | -327.9041 | -113.1613 | -0.8262 | -1.1627 |
0.1114 | 0.5952 | 186 | 0.1125 | 9.6740 | -5.3166 | 1.0 | 14.9906 | -335.8354 | -110.1185 | -0.8446 | -1.2393 |
0.1094 | 0.7936 | 248 | 0.1110 | 9.8335 | -5.4853 | 1.0 | 15.3188 | -337.5219 | -108.5231 | -0.8538 | -1.2560 |
0.1115 | 0.992 | 310 | 0.1100 | 9.9127 | -6.4827 | 1.0 | 16.3954 | -347.4966 | -107.7317 | -0.8658 | -1.3304 |
0.1046 | 1.1904 | 372 | 0.1093 | 9.9819 | -6.6707 | 1.0 | 16.6526 | -349.3765 | -107.0395 | -0.8656 | -1.3633 |
0.1067 | 1.3888 | 434 | 0.1089 | 10.0127 | -7.5740 | 1.0 | 17.5868 | -358.4094 | -106.7308 | -0.8814 | -1.3898 |
0.1038 | 1.5872 | 496 | 0.1083 | 10.0730 | -7.0038 | 1.0 | 17.0768 | -352.7069 | -106.1281 | -0.8755 | -1.3615 |
0.0996 | 1.7856 | 558 | 0.1079 | 10.1219 | -7.0176 | 1.0 | 17.1396 | -352.8456 | -105.6391 | -0.8467 | -1.3431 |
0.1058 | 1.984 | 620 | 0.1077 | 10.1479 | -7.4808 | 1.0 | 17.6287 | -357.4770 | -105.3797 | -0.8821 | -1.4055 |
0.0995 | 2.1824 | 682 | 0.1074 | 10.1669 | -7.1947 | 1.0 | 17.3617 | -354.6166 | -105.1890 | -0.8781 | -1.4102 |
0.1017 | 2.3808 | 744 | 0.1073 | 10.1849 | -7.6243 | 1.0 | 17.8092 | -358.9117 | -105.0093 | -0.8806 | -1.4228 |
0.1031 | 2.5792 | 806 | 0.1072 | 10.2106 | -7.6581 | 1.0 | 17.8687 | -359.2500 | -104.7519 | -0.8787 | -1.4391 |
0.1025 | 2.7776 | 868 | 0.1071 | 10.2105 | -7.6804 | 1.0 | 17.8909 | -359.4730 | -104.7534 | -0.8824 | -1.4506 |
0.1067 | 2.976 | 930 | 0.1071 | 10.2171 | -7.6243 | 1.0 | 17.8413 | -358.9117 | -104.6875 | -0.8781 | -1.4494 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1