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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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datasets: |
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- generator |
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base_model: mistralai/Mixtral-8x7B-v0.1 |
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model-index: |
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- name: Mixtral_dolly_reverse_Inst |
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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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# Mixtral_dolly_reverse_Inst |
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This model is a fine-tuned version of [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4407 |
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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: 2.5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 0.03 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.8058 | 0.05 | 10 | 1.9081 | |
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| 1.7565 | 0.1 | 20 | 1.8383 | |
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| 1.7155 | 0.15 | 30 | 1.7551 | |
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| 1.6477 | 0.2 | 40 | 1.7002 | |
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| 1.5887 | 0.25 | 50 | 1.6647 | |
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| 1.5521 | 0.3 | 60 | 1.6351 | |
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| 1.5184 | 0.35 | 70 | 1.6105 | |
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| 1.5338 | 0.4 | 80 | 1.5860 | |
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| 1.4718 | 0.45 | 90 | 1.5600 | |
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| 1.4739 | 0.5 | 100 | 1.5341 | |
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| 1.4525 | 0.55 | 110 | 1.5110 | |
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| 1.4125 | 0.6 | 120 | 1.4896 | |
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| 1.4118 | 0.65 | 130 | 1.4735 | |
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| 1.3921 | 0.7 | 140 | 1.4631 | |
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| 1.3861 | 0.75 | 150 | 1.4553 | |
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| 1.3765 | 0.8 | 160 | 1.4497 | |
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| 1.3664 | 0.85 | 170 | 1.4460 | |
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| 1.3783 | 0.9 | 180 | 1.4429 | |
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| 1.3544 | 0.95 | 190 | 1.4413 | |
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| 1.3743 | 1.0 | 200 | 1.4407 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
