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--- |
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license: gemma |
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base_model: google/gemma-2b |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: G0514HMA25H |
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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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# G0514HMA25H |
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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: -17.9022 |
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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: 0.0003 |
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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: 16 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 80 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.8009 | 0.09 | 10 | -0.2103 | |
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| -1.0796 | 0.18 | 20 | -2.5087 | |
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| -3.9095 | 0.27 | 30 | -5.8273 | |
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| -7.2606 | 0.36 | 40 | -9.1358 | |
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| -10.3742 | 0.45 | 50 | -12.0428 | |
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| -13.0694 | 0.54 | 60 | -14.4715 | |
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| -15.2349 | 0.63 | 70 | -16.0930 | |
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| -16.5217 | 0.73 | 80 | -16.9969 | |
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| -17.1884 | 0.82 | 90 | -17.3938 | |
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| -17.4707 | 0.91 | 100 | -17.5554 | |
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| -17.5868 | 1.0 | 110 | -17.6315 | |
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| -17.6564 | 1.09 | 120 | -17.6735 | |
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| -17.688 | 1.18 | 130 | -17.7003 | |
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| -17.709 | 1.27 | 140 | -17.7200 | |
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| -17.7262 | 1.36 | 150 | -17.7362 | |
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| -17.7401 | 1.45 | 160 | -17.7476 | |
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| -17.7557 | 1.54 | 170 | -17.7664 | |
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| -17.7777 | 1.63 | 180 | -17.7896 | |
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| -17.7948 | 1.72 | 190 | -17.8078 | |
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| -17.8232 | 1.81 | 200 | -17.8337 | |
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| -17.8393 | 1.9 | 210 | -17.8518 | |
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| -17.8561 | 1.99 | 220 | -17.8679 | |
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| -17.8673 | 2.08 | 230 | -17.8730 | |
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| -17.8748 | 2.18 | 240 | -17.8887 | |
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| -17.8874 | 2.27 | 250 | -17.8931 | |
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| -17.8901 | 2.36 | 260 | -17.8972 | |
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| -17.8918 | 2.45 | 270 | -17.8974 | |
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| -17.8952 | 2.54 | 280 | -17.9002 | |
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| -17.898 | 2.63 | 290 | -17.9012 | |
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| -17.8994 | 2.72 | 300 | -17.9019 | |
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| -17.8999 | 2.81 | 310 | -17.9020 | |
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| -17.9012 | 2.9 | 320 | -17.9022 | |
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| -17.8998 | 2.99 | 330 | -17.9022 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.0 |
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