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Qwen2-7B-Instruct-SPPO-Function-call-v2.9
khongtrunght/Qwen2-7B-Instruct-SPPO-Function-call-v2.9
Qwen2-7B-Instruct-SPPO-Function-call-v2.9 is a machine learning model from khongtrunght. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- qwen2
- Access
- Public
- Created
- Aug 23, 2024
- Updated
- Aug 23, 2024
- SHA
- 708280bc
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
Qwen2-7B-Instruct-SPPO-Function-call-v2.9
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1252
- Rewards/chosen: -1.5039
- Rewards/rejected: -10.1971
- Rewards/accuracies: 0.9422
- Rewards/margins: 8.6931
- Logps/rejected: -449.7067
- Logps/chosen: -174.9095
- Logits/rejected: -1.1951
- Logits/chosen: -1.2269
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1559 | 0.1145 | 250 | 0.1735 | 0.3086 | -3.7350 | 0.9220 | 4.0436 | -320.4661 | -138.6583 | -1.2768 | -1.3532 |
| 0.1173 | 0.2290 | 500 | 0.1548 | -0.3630 | -6.6435 | 0.9364 | 6.2805 | -378.6355 | -152.0903 | -1.2741 | -1.3395 |
| 0.0758 | 0.3436 | 750 | 0.1379 | -0.8688 | -7.9323 | 0.9277 | 7.0635 | -404.4112 | -162.2059 | -1.2435 | -1.2953 |
| 0.0512 | 0.4581 | 1000 | 0.1346 | -1.5788 | -9.3134 | 0.9393 | 7.7346 | -432.0334 | -176.4072 | -1.2333 | -1.2741 |
| 0.1124 | 0.5726 | 1250 | 0.1356 | -1.4131 | -9.8385 | 0.9364 | 8.4254 | -442.5365 | -173.0933 | -1.2057 | -1.2424 |
| 0.0488 | 0.6871 | 1500 | 0.1362 | -1.8112 | -10.5330 | 0.9306 | 8.7217 | -456.4250 | -181.0552 | -1.1979 | -1.2280 |
| 0.1131 | 0.8016 | 1750 | 0.1261 | -1.5432 | -10.1867 | 0.9335 | 8.6435 | -449.5005 | -175.6950 | -1.1964 | -1.2291 |
| 0.0988 | 0.9162 | 2000 | 0.1252 | -1.5039 | -10.1971 | 0.9422 | 8.6931 | -449.7067 | -174.9095 | -1.1951 | -1.2269 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- qwen2
- Created
- Aug 23, 2024
- Updated
- Aug 23, 2024