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--- |
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library_name: peft |
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tags: |
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- alignment-handbook |
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- trl |
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- dpo |
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- generated_from_trainer |
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base_model: NorLLM-AI/NorMistral-7B |
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datasets: |
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- hugodk-sch/aftonposten_title_prefs |
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model-index: |
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- name: norllm-ai-normistral-7b-align-scan |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# norllm-ai-normistral-7b-align-scan |
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This model is a fine-tuned version of [data/norllm-ai-normistral-7b-sft-qlora](https://huggingface.co/data/norllm-ai-normistral-7b-sft-qlora) on the hugodk-sch/aftonposten_title_prefs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8067 |
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- Rewards/chosen: -1.1692 |
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- Rewards/rejected: -1.5184 |
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- Rewards/accuracies: 0.5918 |
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- Rewards/margins: 0.3492 |
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- Logps/rejected: -37.2289 |
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- Logps/chosen: -33.2312 |
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- Logits/rejected: -2.8266 |
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- Logits/chosen: -2.8291 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.6746 | 0.26 | 100 | 0.6828 | 0.0185 | -0.0185 | 0.5694 | 0.0370 | -34.7290 | -31.2516 | -2.8058 | -2.8084 | |
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| 0.6195 | 0.52 | 200 | 0.6735 | -0.0458 | -0.1322 | 0.5511 | 0.0864 | -34.9185 | -31.3587 | -2.8176 | -2.8201 | |
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| 0.5567 | 0.78 | 300 | 0.6810 | -0.1233 | -0.2426 | 0.5723 | 0.1192 | -35.1024 | -31.4880 | -2.8203 | -2.8231 | |
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| 0.2251 | 1.04 | 400 | 0.6779 | -0.3249 | -0.4970 | 0.6013 | 0.1720 | -35.5264 | -31.8240 | -2.8175 | -2.8204 | |
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| 0.2082 | 1.3 | 500 | 0.6859 | -0.4136 | -0.6723 | 0.6092 | 0.2587 | -35.8186 | -31.9717 | -2.8475 | -2.8487 | |
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| 0.2119 | 1.56 | 600 | 0.6993 | -0.5421 | -0.7899 | 0.5926 | 0.2478 | -36.0147 | -32.1860 | -2.8301 | -2.8322 | |
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| 0.1579 | 1.82 | 700 | 0.7178 | -0.6062 | -0.8251 | 0.5806 | 0.2189 | -36.0734 | -32.2928 | -2.8261 | -2.8284 | |
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| 0.0649 | 2.08 | 800 | 0.7260 | -0.7190 | -1.0000 | 0.6071 | 0.2810 | -36.3648 | -32.4808 | -2.8243 | -2.8271 | |
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| 0.1014 | 2.34 | 900 | 0.7758 | -1.0050 | -1.3365 | 0.5831 | 0.3315 | -36.9256 | -32.9574 | -2.8278 | -2.8304 | |
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| 0.0425 | 2.6 | 1000 | 0.7952 | -1.0994 | -1.4459 | 0.5826 | 0.3465 | -37.1080 | -33.1148 | -2.8238 | -2.8267 | |
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| 0.0878 | 2.86 | 1100 | 0.7929 | -1.0931 | -1.4389 | 0.5889 | 0.3458 | -37.0962 | -33.1042 | -2.8257 | -2.8283 | |
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| 0.0534 | 3.12 | 1200 | 0.7997 | -1.1321 | -1.4857 | 0.5889 | 0.3535 | -37.1742 | -33.1693 | -2.8258 | -2.8285 | |
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| 0.035 | 3.38 | 1300 | 0.8024 | -1.1445 | -1.5019 | 0.5889 | 0.3575 | -37.2014 | -33.1899 | -2.8266 | -2.8291 | |
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| 0.0126 | 3.64 | 1400 | 0.8126 | -1.1630 | -1.5088 | 0.5860 | 0.3457 | -37.2128 | -33.2208 | -2.8267 | -2.8294 | |
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| 0.0525 | 3.9 | 1500 | 0.8088 | -1.1685 | -1.5136 | 0.5918 | 0.3451 | -37.2208 | -33.2299 | -2.8265 | -2.8292 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.1 |
