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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: G0521HMA26H5 |
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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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# G0521HMA26H5 |
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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: 0.1040 |
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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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| 1.753 | 0.09 | 10 | 1.3225 | |
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| 0.9976 | 0.18 | 20 | 0.4776 | |
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| 0.3118 | 0.27 | 30 | 0.1654 | |
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| 0.1527 | 0.36 | 40 | 0.1543 | |
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| 0.1481 | 0.45 | 50 | 0.1486 | |
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| 0.1472 | 0.54 | 60 | 0.1495 | |
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| 0.1545 | 0.63 | 70 | 0.1452 | |
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| 0.1467 | 0.73 | 80 | 0.1473 | |
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| 0.1381 | 0.82 | 90 | 0.1348 | |
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| 0.1314 | 0.91 | 100 | 0.1327 | |
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| 0.1316 | 1.0 | 110 | 0.1324 | |
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| 0.1212 | 1.09 | 120 | 0.1323 | |
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| 0.1135 | 1.18 | 130 | 0.1179 | |
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| 0.1188 | 1.27 | 140 | 0.1166 | |
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| 0.1193 | 1.36 | 150 | 0.1179 | |
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| 0.1153 | 1.45 | 160 | 0.1126 | |
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| 0.1145 | 1.54 | 170 | 0.1137 | |
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| 0.1075 | 1.63 | 180 | 0.1109 | |
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| 0.1148 | 1.72 | 190 | 0.1136 | |
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| 0.1126 | 1.81 | 200 | 0.1056 | |
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| 0.1092 | 1.9 | 210 | 0.1042 | |
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| 0.1065 | 1.99 | 220 | 0.1044 | |
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| 0.0961 | 2.08 | 230 | 0.1060 | |
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| 0.0973 | 2.18 | 240 | 0.1027 | |
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| 0.0926 | 2.27 | 250 | 0.1055 | |
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| 0.09 | 2.36 | 260 | 0.1084 | |
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| 0.0916 | 2.45 | 270 | 0.1066 | |
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| 0.0859 | 2.54 | 280 | 0.1057 | |
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| 0.0842 | 2.63 | 290 | 0.1042 | |
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| 0.0855 | 2.72 | 300 | 0.1044 | |
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| 0.0876 | 2.81 | 310 | 0.1045 | |
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| 0.0895 | 2.9 | 320 | 0.1041 | |
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| 0.0896 | 2.99 | 330 | 0.1040 | |
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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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