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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: G0513HMAB1 |
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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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# G0513HMAB1 |
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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: 0.1352 |
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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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| 1.926 | 0.09 | 10 | 1.9074 | |
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| 1.8937 | 0.18 | 20 | 1.8418 | |
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| 1.7669 | 0.27 | 30 | 1.6397 | |
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| 1.4926 | 0.36 | 40 | 1.2660 | |
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| 1.0153 | 0.45 | 50 | 0.6891 | |
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| 0.5171 | 0.54 | 60 | 0.3388 | |
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| 0.2538 | 0.63 | 70 | 0.1816 | |
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| 0.1674 | 0.73 | 80 | 0.1558 | |
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| 0.147 | 0.82 | 90 | 0.1501 | |
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| 0.1461 | 0.91 | 100 | 0.1470 | |
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| 0.1485 | 1.0 | 110 | 0.1488 | |
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| 0.1444 | 1.09 | 120 | 0.1460 | |
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| 0.1446 | 1.18 | 130 | 0.1469 | |
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| 0.1459 | 1.27 | 140 | 0.1454 | |
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| 0.1469 | 1.36 | 150 | 0.1441 | |
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| 0.1404 | 1.45 | 160 | 0.1456 | |
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| 0.142 | 1.54 | 170 | 0.1426 | |
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| 0.1418 | 1.63 | 180 | 0.1418 | |
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| 0.1429 | 1.72 | 190 | 0.1429 | |
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| 0.1401 | 1.81 | 200 | 0.1400 | |
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| 0.1415 | 1.9 | 210 | 0.1392 | |
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| 0.141 | 1.99 | 220 | 0.1395 | |
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| 0.1393 | 2.08 | 230 | 0.1376 | |
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| 0.137 | 2.18 | 240 | 0.1374 | |
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| 0.1349 | 2.27 | 250 | 0.1368 | |
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| 0.1392 | 2.36 | 260 | 0.1367 | |
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| 0.1369 | 2.45 | 270 | 0.1364 | |
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| 0.1337 | 2.54 | 280 | 0.1360 | |
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| 0.1322 | 2.63 | 290 | 0.1356 | |
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| 0.1341 | 2.72 | 300 | 0.1353 | |
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| 0.1349 | 2.81 | 310 | 0.1352 | |
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| 0.1343 | 2.9 | 320 | 0.1352 | |
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| 0.1365 | 2.99 | 330 | 0.1352 | |
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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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