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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: G0513HMA1H |
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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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# G0513HMA1H |
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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: 0.1331 |
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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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| 3.1824 | 0.09 | 10 | 2.8991 | |
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| 2.6535 | 0.18 | 20 | 2.2337 | |
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| 1.8658 | 0.27 | 30 | 1.4097 | |
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| 1.0771 | 0.36 | 40 | 0.6675 | |
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| 0.4164 | 0.45 | 50 | 0.2215 | |
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| 0.1854 | 0.54 | 60 | 0.1678 | |
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| 0.1586 | 0.63 | 70 | 0.1549 | |
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| 0.153 | 0.73 | 80 | 0.1504 | |
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| 0.1434 | 0.82 | 90 | 0.1510 | |
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| 0.1463 | 0.91 | 100 | 0.1488 | |
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| 0.1487 | 1.0 | 110 | 0.1499 | |
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| 0.1439 | 1.09 | 120 | 0.1488 | |
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| 0.1454 | 1.18 | 130 | 0.1481 | |
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| 0.1456 | 1.27 | 140 | 0.1468 | |
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| 0.148 | 1.36 | 150 | 0.1459 | |
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| 0.1426 | 1.45 | 160 | 0.1489 | |
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| 0.1441 | 1.54 | 170 | 0.1468 | |
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| 0.1447 | 1.63 | 180 | 0.1448 | |
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| 0.1456 | 1.72 | 190 | 0.1494 | |
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| 0.1454 | 1.81 | 200 | 0.1461 | |
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| 0.1448 | 1.9 | 210 | 0.1451 | |
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| 0.1454 | 1.99 | 220 | 0.1436 | |
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| 0.1406 | 2.08 | 230 | 0.1407 | |
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| 0.136 | 2.18 | 240 | 0.1395 | |
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| 0.1345 | 2.27 | 250 | 0.1406 | |
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| 0.1392 | 2.36 | 260 | 0.1384 | |
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| 0.1356 | 2.45 | 270 | 0.1367 | |
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| 0.1343 | 2.54 | 280 | 0.1357 | |
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| 0.1313 | 2.63 | 290 | 0.1344 | |
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| 0.13 | 2.72 | 300 | 0.1331 | |
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| 0.1356 | 2.81 | 310 | 0.1330 | |
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| 0.1338 | 2.9 | 320 | 0.1330 | |
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| 0.1323 | 2.99 | 330 | 0.1331 | |
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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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