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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: G0428HMA5 |
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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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# G0428HMA5 |
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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: 0.1085 |
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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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| 2.7283 | 0.09 | 10 | 1.9180 | |
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| 1.3514 | 0.18 | 20 | 0.6885 | |
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| 0.3688 | 0.27 | 30 | 0.1812 | |
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| 0.1614 | 0.36 | 40 | 0.1524 | |
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| 0.1477 | 0.45 | 50 | 0.1476 | |
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| 0.1475 | 0.54 | 60 | 0.1480 | |
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| 0.1477 | 0.63 | 70 | 0.1475 | |
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| 0.1481 | 0.73 | 80 | 0.1481 | |
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| 0.1415 | 0.82 | 90 | 0.1487 | |
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| 0.1455 | 0.91 | 100 | 0.1473 | |
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| 0.1484 | 1.0 | 110 | 0.1482 | |
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| 0.143 | 1.09 | 120 | 0.1482 | |
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| 0.1441 | 1.18 | 130 | 0.1479 | |
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| 0.1452 | 1.27 | 140 | 0.1453 | |
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| 0.1464 | 1.36 | 150 | 0.1433 | |
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| 0.1394 | 1.45 | 160 | 0.1517 | |
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| 0.1425 | 1.54 | 170 | 0.1415 | |
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| 0.1378 | 1.63 | 180 | 0.1336 | |
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| 0.1322 | 1.72 | 190 | 0.1349 | |
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| 0.1269 | 1.81 | 200 | 0.1243 | |
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| 0.1255 | 1.9 | 210 | 0.1209 | |
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| 0.1212 | 1.99 | 220 | 0.1208 | |
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| 0.1115 | 2.08 | 230 | 0.1180 | |
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| 0.1151 | 2.18 | 240 | 0.1169 | |
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| 0.1089 | 2.27 | 250 | 0.1160 | |
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| 0.1085 | 2.36 | 260 | 0.1134 | |
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| 0.1099 | 2.45 | 270 | 0.1118 | |
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| 0.1031 | 2.54 | 280 | 0.1112 | |
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| 0.0986 | 2.63 | 290 | 0.1099 | |
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| 0.1008 | 2.72 | 300 | 0.1091 | |
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| 0.1075 | 2.81 | 310 | 0.1087 | |
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| 0.1048 | 2.9 | 320 | 0.1085 | |
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| 0.1047 | 2.99 | 330 | 0.1085 | |
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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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