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--- |
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license: gemma |
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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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base_model: google/gemma-2b |
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model-index: |
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- name: gemma-2b-it-gee |
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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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# gemma-2b-it-gee |
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This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9609 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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- training_steps: 200 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| No log | 0.016 | 2 | 1.1482 | |
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| No log | 0.032 | 4 | 1.1330 | |
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| No log | 0.048 | 6 | 1.1206 | |
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| No log | 0.064 | 8 | 1.1111 | |
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| No log | 0.08 | 10 | 1.1005 | |
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| No log | 0.096 | 12 | 1.0913 | |
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| No log | 0.112 | 14 | 1.0823 | |
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| No log | 0.128 | 16 | 1.0734 | |
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| No log | 0.144 | 18 | 1.0660 | |
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| No log | 0.16 | 20 | 1.0590 | |
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| No log | 0.176 | 22 | 1.0520 | |
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| No log | 0.192 | 24 | 1.0470 | |
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| No log | 0.208 | 26 | 1.0425 | |
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| No log | 0.224 | 28 | 1.0387 | |
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| No log | 0.24 | 30 | 1.0353 | |
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| No log | 0.256 | 32 | 1.0320 | |
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| No log | 0.272 | 34 | 1.0288 | |
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| No log | 0.288 | 36 | 1.0256 | |
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| No log | 0.304 | 38 | 1.0232 | |
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| No log | 0.32 | 40 | 1.0204 | |
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| No log | 0.336 | 42 | 1.0183 | |
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| No log | 0.352 | 44 | 1.0159 | |
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| No log | 0.368 | 46 | 1.0137 | |
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| No log | 0.384 | 48 | 1.0115 | |
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| 1.0621 | 0.4 | 50 | 1.0095 | |
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| 1.0621 | 0.416 | 52 | 1.0075 | |
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| 1.0621 | 0.432 | 54 | 1.0054 | |
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| 1.0621 | 0.448 | 56 | 1.0034 | |
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| 1.0621 | 0.464 | 58 | 1.0014 | |
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| 1.0621 | 0.48 | 60 | 0.9994 | |
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| 1.0621 | 0.496 | 62 | 0.9976 | |
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| 1.0621 | 0.512 | 64 | 0.9960 | |
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| 1.0621 | 0.528 | 66 | 0.9944 | |
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| 1.0621 | 0.544 | 68 | 0.9928 | |
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| 1.0621 | 0.56 | 70 | 0.9911 | |
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| 1.0621 | 0.576 | 72 | 0.9896 | |
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| 1.0621 | 0.592 | 74 | 0.9882 | |
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| 1.0621 | 0.608 | 76 | 0.9868 | |
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| 1.0621 | 0.624 | 78 | 0.9853 | |
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| 1.0621 | 0.64 | 80 | 0.9836 | |
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| 1.0621 | 0.656 | 82 | 0.9822 | |
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| 1.0621 | 0.672 | 84 | 0.9809 | |
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| 1.0621 | 0.688 | 86 | 0.9797 | |
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| 1.0621 | 0.704 | 88 | 0.9785 | |
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| 1.0621 | 0.72 | 90 | 0.9775 | |
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| 1.0621 | 0.736 | 92 | 0.9764 | |
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| 1.0621 | 0.752 | 94 | 0.9754 | |
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| 1.0621 | 0.768 | 96 | 0.9745 | |
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| 1.0621 | 0.784 | 98 | 0.9737 | |
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| 1.0035 | 0.8 | 100 | 0.9729 | |
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| 1.0035 | 0.816 | 102 | 0.9723 | |
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| 1.0035 | 0.832 | 104 | 0.9716 | |
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| 1.0035 | 0.848 | 106 | 0.9710 | |
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| 1.0035 | 0.864 | 108 | 0.9705 | |
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| 1.0035 | 0.88 | 110 | 0.9700 | |
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| 1.0035 | 0.896 | 112 | 0.9695 | |
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| 1.0035 | 0.912 | 114 | 0.9690 | |
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| 1.0035 | 0.928 | 116 | 0.9685 | |
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| 1.0035 | 0.944 | 118 | 0.9681 | |
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| 1.0035 | 0.96 | 120 | 0.9677 | |
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| 1.0035 | 0.976 | 122 | 0.9674 | |
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| 1.0035 | 0.992 | 124 | 0.9671 | |
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| 1.0035 | 1.008 | 126 | 0.9668 | |
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| 1.0035 | 1.024 | 128 | 0.9665 | |
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| 1.0035 | 1.04 | 130 | 0.9661 | |
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| 1.0035 | 1.056 | 132 | 0.9657 | |
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| 1.0035 | 1.072 | 134 | 0.9654 | |
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| 1.0035 | 1.088 | 136 | 0.9652 | |
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| 1.0035 | 1.104 | 138 | 0.9650 | |
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| 1.0035 | 1.12 | 140 | 0.9648 | |
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| 1.0035 | 1.1360 | 142 | 0.9645 | |
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| 1.0035 | 1.152 | 144 | 0.9644 | |
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| 1.0035 | 1.168 | 146 | 0.9642 | |
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| 1.0035 | 1.184 | 148 | 0.9639 | |
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| 0.9687 | 1.2 | 150 | 0.9637 | |
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| 0.9687 | 1.216 | 152 | 0.9634 | |
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| 0.9687 | 1.232 | 154 | 0.9632 | |
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| 0.9687 | 1.248 | 156 | 0.9630 | |
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| 0.9687 | 1.264 | 158 | 0.9628 | |
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| 0.9687 | 1.28 | 160 | 0.9627 | |
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| 0.9687 | 1.296 | 162 | 0.9625 | |
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| 0.9687 | 1.312 | 164 | 0.9623 | |
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| 0.9687 | 1.328 | 166 | 0.9622 | |
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| 0.9687 | 1.3440 | 168 | 0.9620 | |
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| 0.9687 | 1.3600 | 170 | 0.9619 | |
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| 0.9687 | 1.376 | 172 | 0.9618 | |
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| 0.9687 | 1.392 | 174 | 0.9617 | |
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| 0.9687 | 1.408 | 176 | 0.9616 | |
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| 0.9687 | 1.424 | 178 | 0.9615 | |
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| 0.9687 | 1.44 | 180 | 0.9614 | |
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| 0.9687 | 1.456 | 182 | 0.9613 | |
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| 0.9687 | 1.472 | 184 | 0.9613 | |
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| 0.9687 | 1.488 | 186 | 0.9612 | |
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| 0.9687 | 1.504 | 188 | 0.9611 | |
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| 0.9687 | 1.52 | 190 | 0.9611 | |
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| 0.9687 | 1.536 | 192 | 0.9610 | |
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| 0.9687 | 1.552 | 194 | 0.9610 | |
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| 0.9687 | 1.568 | 196 | 0.9609 | |
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| 0.9687 | 1.584 | 198 | 0.9609 | |
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| 0.982 | 1.6 | 200 | 0.9609 | |
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### Framework versions |
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- PEFT 0.10.1.dev0 |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
