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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: G0521HMA26H3 |
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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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# G0521HMA26H3 |
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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: 0.1116 |
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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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| 1.7533 | 0.09 | 10 | 1.3694 | |
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| 1.0332 | 0.18 | 20 | 0.5170 | |
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| 0.3393 | 0.27 | 30 | 0.1684 | |
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| 0.1539 | 0.36 | 40 | 0.1588 | |
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| 0.1472 | 0.45 | 50 | 0.1883 | |
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| 0.1478 | 0.54 | 60 | 0.1928 | |
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| 0.1446 | 0.63 | 70 | 0.1654 | |
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| 0.1449 | 0.73 | 80 | 0.1611 | |
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| 0.1354 | 0.82 | 90 | 0.1416 | |
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| 0.1272 | 0.91 | 100 | 0.1641 | |
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| 0.1286 | 1.0 | 110 | 0.1561 | |
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| 0.1189 | 1.09 | 120 | 0.1664 | |
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| 0.1125 | 1.18 | 130 | 0.1229 | |
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| 0.116 | 1.27 | 140 | 0.1370 | |
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| 0.1185 | 1.36 | 150 | 0.1270 | |
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| 0.1168 | 1.45 | 160 | 0.1343 | |
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| 0.1089 | 1.54 | 170 | 0.1347 | |
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| 0.1095 | 1.63 | 180 | 0.1379 | |
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| 0.1104 | 1.72 | 190 | 0.1308 | |
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| 0.1101 | 1.81 | 200 | 0.1568 | |
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| 0.1101 | 1.9 | 210 | 0.1091 | |
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| 0.1069 | 1.99 | 220 | 0.1196 | |
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| 0.0933 | 2.08 | 230 | 0.1193 | |
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| 0.0961 | 2.18 | 240 | 0.1171 | |
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| 0.091 | 2.27 | 250 | 0.1358 | |
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| 0.0906 | 2.36 | 260 | 0.1123 | |
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| 0.0914 | 2.45 | 270 | 0.1114 | |
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| 0.0833 | 2.54 | 280 | 0.1243 | |
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| 0.0827 | 2.63 | 290 | 0.1207 | |
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| 0.0836 | 2.72 | 300 | 0.1153 | |
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| 0.0858 | 2.81 | 310 | 0.1132 | |
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| 0.0874 | 2.9 | 320 | 0.1114 | |
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| 0.0926 | 2.99 | 330 | 0.1116 | |
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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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