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Model: afrideva/zephyr-220m-sft-full-GGUF Source: Original Platform
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README.md
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---
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base_model: BEE-spoke-data/zephyr-220m-sft-full
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datasets:
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- HuggingFaceH4/ultrachat_200k
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inference: false
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license: apache-2.0
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model-index:
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- name: zephyr-220m-sft-full
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results: []
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model_creator: BEE-spoke-data
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model_name: zephyr-220m-sft-full
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pipeline_tag: text-generation
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quantized_by: afrideva
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tags:
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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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- q2_k
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- q3_k_m
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- q4_k_m
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- q5_k_m
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- q6_k
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- q8_0
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---
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# BEE-spoke-data/zephyr-220m-sft-full-GGUF
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Quantized GGUF model files for [zephyr-220m-sft-full](https://huggingface.co/BEE-spoke-data/zephyr-220m-sft-full) from [BEE-spoke-data](https://huggingface.co/BEE-spoke-data)
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| Name | Quant method | Size |
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| ---- | ---- | ---- |
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| [zephyr-220m-sft-full.fp16.gguf](https://huggingface.co/afrideva/zephyr-220m-sft-full-GGUF/resolve/main/zephyr-220m-sft-full.fp16.gguf) | fp16 | 436.50 MB |
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| [zephyr-220m-sft-full.q2_k.gguf](https://huggingface.co/afrideva/zephyr-220m-sft-full-GGUF/resolve/main/zephyr-220m-sft-full.q2_k.gguf) | q2_k | 94.43 MB |
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| [zephyr-220m-sft-full.q3_k_m.gguf](https://huggingface.co/afrideva/zephyr-220m-sft-full-GGUF/resolve/main/zephyr-220m-sft-full.q3_k_m.gguf) | q3_k_m | 114.65 MB |
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| [zephyr-220m-sft-full.q4_k_m.gguf](https://huggingface.co/afrideva/zephyr-220m-sft-full-GGUF/resolve/main/zephyr-220m-sft-full.q4_k_m.gguf) | q4_k_m | 137.58 MB |
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| [zephyr-220m-sft-full.q5_k_m.gguf](https://huggingface.co/afrideva/zephyr-220m-sft-full-GGUF/resolve/main/zephyr-220m-sft-full.q5_k_m.gguf) | q5_k_m | 157.91 MB |
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| [zephyr-220m-sft-full.q6_k.gguf](https://huggingface.co/afrideva/zephyr-220m-sft-full-GGUF/resolve/main/zephyr-220m-sft-full.q6_k.gguf) | q6_k | 179.52 MB |
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| [zephyr-220m-sft-full.q8_0.gguf](https://huggingface.co/afrideva/zephyr-220m-sft-full-GGUF/resolve/main/zephyr-220m-sft-full.q8_0.gguf) | q8_0 | 232.28 MB |
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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-220m-sft-full
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This model is a fine-tuned version of [BEE-spoke-data/smol_llama-220M-openhermes](https://huggingface.co/BEE-spoke-data/smol_llama-220M-openhermes) on the Ultrachat_200k dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6579
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 32
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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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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.6447 | 1.0 | 1624 | 1.6579 |
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### Framework versions
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- Transformers 4.37.0.dev0
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- Pytorch 2.1.2+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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https://wandb.ai/amazingvince/huggingface/runs/5rffzk3x/workspace?workspace=user-amazingvince
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