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--- |
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library_name: peft |
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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: gemma2-mentalchat16k |
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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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# gemma2-mentalchat16k |
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This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7946 |
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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: 0.0002 |
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- train_batch_size: 3 |
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- eval_batch_size: 3 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 6 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 4 |
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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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| 1.0076 | 0.1122 | 100 | 0.9827 | |
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| 0.9399 | 0.2243 | 200 | 0.9345 | |
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| 0.9054 | 0.3365 | 300 | 0.9031 | |
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| 0.8561 | 0.4487 | 400 | 0.8859 | |
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| 0.8794 | 0.5609 | 500 | 0.8711 | |
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| 0.844 | 0.6730 | 600 | 0.8557 | |
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| 0.8305 | 0.7852 | 700 | 0.8461 | |
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| 0.8207 | 0.8974 | 800 | 0.8400 | |
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| 0.8117 | 1.0090 | 900 | 0.8529 | |
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| 0.7338 | 1.1211 | 1000 | 0.8448 | |
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| 0.7422 | 1.2333 | 1100 | 0.8332 | |
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| 0.6964 | 1.3455 | 1200 | 0.8273 | |
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| 0.7064 | 1.4577 | 1300 | 0.8252 | |
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| 0.7201 | 1.5698 | 1400 | 0.8170 | |
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| 0.7162 | 1.6820 | 1500 | 0.8121 | |
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| 0.688 | 1.7942 | 1600 | 0.8088 | |
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| 0.7166 | 1.9063 | 1700 | 0.7998 | |
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| 0.636 | 2.0179 | 1800 | 0.8447 | |
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| 0.5388 | 2.1301 | 1900 | 0.8485 | |
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| 0.5319 | 2.2423 | 2000 | 0.8444 | |
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| 0.5396 | 2.3545 | 2100 | 0.8498 | |
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| 0.5523 | 2.4666 | 2200 | 0.8446 | |
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### Framework versions |
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- PEFT 0.15.2 |
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- Transformers 4.54.1 |
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- Pytorch 2.7.1+cu118 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
