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README.md
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---
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base_model: masakhane/zephyr-7b-gemma-sft-african-ultrachat-200k
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datasets:
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- masakhane/african-ultrachat
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- israel/untrachat_en
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inference: true
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license: gemma
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model-index:
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- name: zephyr-7b-gemma-sft-african-ultrachat-2000k
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results: []
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model_creator: masakhane
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model_name: zephyr-7b-gemma-sft-african-ultrachat-200k
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pipeline_tag: text-generation
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quantized_by: afrideva
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tags:
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- alignment-handbook
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- trl
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- sft
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- generated_from_trainer
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- trl
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- sft
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- generated_from_trainer
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- gguf
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- ggml
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- quantized
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---
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# zephyr-7b-gemma-sft-african-ultrachat-200k-GGUF
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Quantized GGUF model files for [zephyr-7b-gemma-sft-african-ultrachat-200k](https://huggingface.co/masakhane/zephyr-7b-gemma-sft-african-ultrachat-200k) from [masakhane](https://huggingface.co/masakhane)
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## Original Model Card:
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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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# zephyr-7b-gemma-sft-african-ultrachat-2000k
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This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the masakhane/african-ultrachat and the israel/untrachat_en datasets.
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It achieves the following results on the evaluation set:
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- Loss: 1.1549
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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: 1e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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- total_eval_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 1.0785 | 1.0 | 17748 | 1.2602 |
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| 0.6614 | 2.0 | 35496 | 1.1089 |
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| 0.2983 | 3.0 | 53244 | 1.1549 |
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### Framework versions
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- Transformers 4.39.0.dev0
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- Pytorch 2.2.1+cu121
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- Datasets 2.14.6
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- Tokenizers 0.15.2
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