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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+zephyr-7b-gemma-sft-v0.1 - bnb 4bits
+- Model creator: https://huggingface.co/HuggingFaceH4/
+- Original model: https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-sft-v0.1/
+
+
+
+
+Original model description:
+---
+license: other
+license_name: gemma-terms-of-use
+license_link: https://ai.google.dev/gemma/terms
+base_model: google/gemma-7b
+tags:
+- alignment-handbook
+- trl
+- sft
+- generated_from_trainer
+- trl
+- sft
+- generated_from_trainer
+datasets:
+- HuggingFaceH4/deita-10k-v0-sft
+model-index:
+- name: zephyr-7b-gemma-sft
+  results: []
+language:
+- en
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# zephyr-7b-gemma-sft
+
+This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the HuggingFaceH4/deita-10k-v0-sft dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9732
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 16
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 128
+- total_eval_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.9482        | 1.0   | 299  | 0.9848          |
+| 0.8139        | 2.0   | 599  | 0.9610          |
+| 0.722         | 2.99  | 897  | 0.9732          |
+
+
+### Framework versions
+
+- Transformers 4.39.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.14.6
+- Tokenizers 0.15.1
+