afrideva
/

zephyr-smol_llama-100m-dpo-full-GGUF

+---
+base_model: amazingvince/zephyr-smol_llama-100m-dpo-full
+inference: false
+license: apache-2.0
+model-index:
+- name: zephyr-smol_llama-100m-dpo-full
+  results: []
+model_creator: amazingvince
+model_name: zephyr-smol_llama-100m-dpo-full
+pipeline_tag: text-generation
+quantized_by: afrideva
+tags:
+- generated_from_trainer
+- gguf
+- ggml
+- quantized
+- q2_k
+- q3_k_m
+- q4_k_m
+- q5_k_m
+- q6_k
+- q8_0
+---
+# amazingvince/zephyr-smol_llama-100m-dpo-full-GGUF
+Quantized GGUF model files for [zephyr-smol_llama-100m-dpo-full](https://huggingface.co/amazingvince/zephyr-smol_llama-100m-dpo-full) from [amazingvince](https://huggingface.co/amazingvince)
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [zephyr-smol_llama-100m-dpo-full.fp16.gguf](https://huggingface.co/afrideva/zephyr-smol_llama-100m-dpo-full-GGUF/resolve/main/zephyr-smol_llama-100m-dpo-full.fp16.gguf) | fp16 | 204.25 MB  |
+| [zephyr-smol_llama-100m-dpo-full.q2_k.gguf](https://huggingface.co/afrideva/zephyr-smol_llama-100m-dpo-full-GGUF/resolve/main/zephyr-smol_llama-100m-dpo-full.q2_k.gguf) | q2_k | 51.90 MB  |
+| [zephyr-smol_llama-100m-dpo-full.q3_k_m.gguf](https://huggingface.co/afrideva/zephyr-smol_llama-100m-dpo-full-GGUF/resolve/main/zephyr-smol_llama-100m-dpo-full.q3_k_m.gguf) | q3_k_m | 58.04 MB  |
+| [zephyr-smol_llama-100m-dpo-full.q4_k_m.gguf](https://huggingface.co/afrideva/zephyr-smol_llama-100m-dpo-full-GGUF/resolve/main/zephyr-smol_llama-100m-dpo-full.q4_k_m.gguf) | q4_k_m | 66.38 MB  |
+| [zephyr-smol_llama-100m-dpo-full.q5_k_m.gguf](https://huggingface.co/afrideva/zephyr-smol_llama-100m-dpo-full-GGUF/resolve/main/zephyr-smol_llama-100m-dpo-full.q5_k_m.gguf) | q5_k_m | 75.31 MB  |
+| [zephyr-smol_llama-100m-dpo-full.q6_k.gguf](https://huggingface.co/afrideva/zephyr-smol_llama-100m-dpo-full-GGUF/resolve/main/zephyr-smol_llama-100m-dpo-full.q6_k.gguf) | q6_k | 84.80 MB  |
+| [zephyr-smol_llama-100m-dpo-full.q8_0.gguf](https://huggingface.co/afrideva/zephyr-smol_llama-100m-dpo-full-GGUF/resolve/main/zephyr-smol_llama-100m-dpo-full.q8_0.gguf) | q8_0 | 109.33 MB  |
+## Original Model Card:
+<!-- 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-smol_llama-100m-dpo-full
+This model is a fine-tuned version of [amazingvince/zephyr-smol_llama-100m-sft-full](https://huggingface.co/amazingvince/zephyr-smol_llama-100m-sft-full) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5465
+- Rewards/chosen: -0.0518
+- Rewards/rejected: -0.7661
+- Rewards/accuracies: 0.7170
+- Rewards/margins: 0.7143
+- Logps/rejected: -450.2018
+- Logps/chosen: -588.7877
+- Logits/rejected: -4.9602
+- Logits/chosen: -5.2468
+## 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: 5e-07
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- total_train_batch_size: 16
+- total_eval_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:-----:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.6549        | 0.26  | 1000  | 0.6037          | -0.1205        | -0.4850          | 0.6550             | 0.3644          | -447.3903      | -589.4750    | -4.7410         | -5.0341       |
+| 0.5349        | 0.52  | 2000  | 0.5779          | -0.0126        | -0.5080          | 0.6770             | 0.4955          | -447.6208      | -588.3951    | -4.8645         | -5.1463       |
+| 0.6029        | 0.77  | 3000  | 0.5657          | 0.0902         | -0.4636          | 0.6900             | 0.5538          | -447.1767      | -587.3674    | -5.0016         | -5.2911       |
+| 0.5273        | 1.03  | 4000  | 0.5596          | 0.0496         | -0.5449          | 0.7040             | 0.5944          | -447.9891      | -587.7738    | -4.9972         | -5.2892       |
+| 0.5           | 1.29  | 5000  | 0.5557          | 0.0585         | -0.6110          | 0.7050             | 0.6695          | -448.6505      | -587.6843    | -5.0108         | -5.3047       |
+| 0.5056        | 1.55  | 6000  | 0.5499          | 0.0054         | -0.6719          | 0.7130             | 0.6773          | -449.2598      | -588.2154    | -4.9988         | -5.2907       |
+| 0.4608        | 1.81  | 7000  | 0.5500          | -0.0376        | -0.7494          | 0.7030             | 0.7118          | -450.0341      | -588.6455    | -5.0549         | -5.3406       |
+| 0.426         | 2.07  | 8000  | 0.5472          | -0.0106        | -0.7021          | 0.7100             | 0.6916          | -449.5617      | -588.3751    | -4.9750         | -5.2626       |
+| 0.3875        | 2.32  | 9000  | 0.5464          | -0.0011        | -0.7171          | 0.7140             | 0.7159          | -449.7113      | -588.2810    | -4.9935         | -5.2796       |
+| 0.397         | 2.58  | 10000 | 0.5462          | -0.0391        | -0.7566          | 0.7190             | 0.7175          | -450.1064      | -588.6602    | -4.9737         | -5.2618       |
+| 0.4486        | 2.84  | 11000 | 0.5459          | -0.0493        | -0.7667          | 0.7110             | 0.7174          | -450.2074      | -588.7629    | -4.9569         | -5.2441       |
+### Framework versions
+- Transformers 4.35.0
+- Pytorch 2.1.0
+- Datasets 2.14.6
+- Tokenizers 0.14.1