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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: G0428HMA4 |
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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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# G0428HMA4 |
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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: 0.1167 |
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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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| 2.8227 | 0.09 | 10 | 2.1171 | |
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| 1.6416 | 0.18 | 20 | 1.0605 | |
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| 0.6589 | 0.27 | 30 | 0.2594 | |
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| 0.1907 | 0.36 | 40 | 0.1623 | |
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| 0.1539 | 0.45 | 50 | 0.1509 | |
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| 0.1503 | 0.54 | 60 | 0.1492 | |
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| 0.1479 | 0.63 | 70 | 0.1475 | |
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| 0.1494 | 0.73 | 80 | 0.1482 | |
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| 0.1415 | 0.82 | 90 | 0.1490 | |
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| 0.1453 | 0.91 | 100 | 0.1474 | |
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| 0.1486 | 1.0 | 110 | 0.1482 | |
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| 0.1426 | 1.09 | 120 | 0.1473 | |
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| 0.1437 | 1.18 | 130 | 0.1473 | |
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| 0.1444 | 1.27 | 140 | 0.1464 | |
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| 0.1468 | 1.36 | 150 | 0.1456 | |
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| 0.1422 | 1.45 | 160 | 0.1481 | |
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| 0.143 | 1.54 | 170 | 0.1451 | |
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| 0.1426 | 1.63 | 180 | 0.1438 | |
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| 0.1436 | 1.72 | 190 | 0.1450 | |
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| 0.1398 | 1.81 | 200 | 0.1374 | |
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| 0.1353 | 1.9 | 210 | 0.1372 | |
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| 0.1339 | 1.99 | 220 | 0.1310 | |
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| 0.1229 | 2.08 | 230 | 0.1288 | |
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| 0.1229 | 2.18 | 240 | 0.1268 | |
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| 0.1209 | 2.27 | 250 | 0.1251 | |
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| 0.1238 | 2.36 | 260 | 0.1220 | |
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| 0.1223 | 2.45 | 270 | 0.1222 | |
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| 0.1151 | 2.54 | 280 | 0.1208 | |
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| 0.1131 | 2.63 | 290 | 0.1182 | |
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| 0.1129 | 2.72 | 300 | 0.1173 | |
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| 0.113 | 2.81 | 310 | 0.1168 | |
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| 0.1162 | 2.9 | 320 | 0.1167 | |
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| 0.1152 | 2.99 | 330 | 0.1167 | |
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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 0.14.1 |
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