mpt_1000_STEPS_1e8_rate_03_beta_DPO
This model is a fine-tuned version of mosaicml/mpt-7b-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6941
- Rewards/chosen: -1.2875
- Rewards/rejected: -1.6132
- Rewards/accuracies: 0.6154
- Rewards/margins: 0.3257
- Logps/rejected: -24.7839
- Logps/chosen: -23.3672
- Logits/rejected: 14.1648
- Logits/chosen: 14.1681
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-06
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.7473 | 0.1 | 100 | 0.6927 | 0.1811 | 0.1159 | 0.5582 | 0.0651 | -21.3256 | -20.4301 | 14.3166 | 14.3195 |
| 0.7098 | 0.2 | 200 | 0.7624 | 0.6571 | 0.5345 | 0.5714 | 0.1226 | -20.4884 | -19.4780 | 14.1537 | 14.1566 |
| 0.7516 | 0.29 | 300 | 0.7505 | -0.8487 | -1.0927 | 0.5429 | 0.2440 | -23.7428 | -22.4895 | 14.5590 | 14.5620 |
| 0.7762 | 0.39 | 400 | 0.7476 | -2.2343 | -2.4798 | 0.5692 | 0.2455 | -26.5171 | -25.2608 | 14.0064 | 14.0094 |
| 0.8328 | 0.49 | 500 | 0.7228 | -1.5283 | -1.7877 | 0.5736 | 0.2594 | -25.1329 | -23.8488 | 14.1811 | 14.1843 |
| 0.625 | 0.59 | 600 | 0.7006 | -1.3183 | -1.6353 | 0.5978 | 0.3170 | -24.8281 | -23.4288 | 14.3453 | 14.3486 |
| 0.7164 | 0.68 | 700 | 0.7015 | -1.2944 | -1.6029 | 0.6022 | 0.3084 | -24.7632 | -23.3811 | 14.2239 | 14.2271 |
| 0.6844 | 0.78 | 800 | 0.6985 | -1.2758 | -1.5914 | 0.6198 | 0.3157 | -24.7403 | -23.3437 | 14.1630 | 14.1663 |
| 0.6996 | 0.88 | 900 | 0.6971 | -1.2896 | -1.6092 | 0.6110 | 0.3196 | -24.7758 | -23.3713 | 14.1673 | 14.1706 |
| 0.6352 | 0.98 | 1000 | 0.6941 | -1.2875 | -1.6132 | 0.6154 | 0.3257 | -24.7839 | -23.3672 | 14.1648 | 14.1681 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
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