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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: G0428HMA17
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+ results: []
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+ ---
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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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+
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+ # G0428HMA17
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+
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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: 0.1475
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 60
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+ - num_epochs: 3
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 2.4638 | 0.09 | 10 | 1.3793 |
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+ | 0.7418 | 0.18 | 20 | 0.2028 |
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+ | 0.1674 | 0.27 | 30 | 0.1537 |
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+ | 0.1515 | 0.36 | 40 | 0.1513 |
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+ | 0.1467 | 0.45 | 50 | 0.1468 |
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+ | 0.1476 | 0.54 | 60 | 0.1490 |
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+ | 0.1497 | 0.63 | 70 | 0.1493 |
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+ | 0.1505 | 0.73 | 80 | 0.1493 |
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+ | 0.1436 | 0.82 | 90 | 0.1560 |
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+ | 0.1488 | 0.91 | 100 | 0.1536 |
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+ | 0.1518 | 1.0 | 110 | 0.1515 |
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+ | 0.1436 | 1.09 | 120 | 0.1541 |
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+ | 0.1891 | 1.18 | 130 | 0.1701 |
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+ | 0.1629 | 1.27 | 140 | 0.1505 |
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+ | 0.1532 | 1.36 | 150 | 0.1500 |
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+ | 0.1458 | 1.45 | 160 | 0.1529 |
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+ | 0.1515 | 1.54 | 170 | 0.1505 |
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+ | 0.1493 | 1.63 | 180 | 0.1487 |
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+ | 0.1484 | 1.72 | 190 | 0.1506 |
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+ | 0.1474 | 1.81 | 200 | 0.1488 |
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+ | 0.1484 | 1.9 | 210 | 0.1474 |
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+ | 0.1477 | 1.99 | 220 | 0.1485 |
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+ | 0.1459 | 2.08 | 230 | 0.1478 |
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+ | 0.1467 | 2.18 | 240 | 0.1494 |
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+ | 0.1459 | 2.27 | 250 | 0.1479 |
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+ | 0.1471 | 2.36 | 260 | 0.1482 |
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+ | 0.1446 | 2.45 | 270 | 0.1478 |
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+ | 0.144 | 2.54 | 280 | 0.1479 |
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+ | 0.1445 | 2.63 | 290 | 0.1478 |
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+ | 0.1455 | 2.72 | 300 | 0.1476 |
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+ | 0.1459 | 2.81 | 310 | 0.1475 |
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+ | 0.1454 | 2.9 | 320 | 0.1475 |
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+ | 0.1467 | 2.99 | 330 | 0.1475 |
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+
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+
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+ ### Framework versions
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+
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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 0.14.1
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