afrideva
/

phi-2_dolly_instruction_polish-GGUF

+---
+base_model: s3nh/phi-2_dolly_instruction_polish
+inference: false
+library_name: peft
+license: other
+model-index:
+- name: phi-2-sft-out
+  results: []
+model_creator: s3nh
+model_name: phi-2_dolly_instruction_polish
+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
+---
+# s3nh/phi-2_dolly_instruction_polish-GGUF
+Quantized GGUF model files for [phi-2_dolly_instruction_polish](https://huggingface.co/s3nh/phi-2_dolly_instruction_polish) from [s3nh](https://huggingface.co/s3nh)
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [phi-2_dolly_instruction_polish.fp16.gguf](https://huggingface.co/afrideva/phi-2_dolly_instruction_polish-GGUF/resolve/main/phi-2_dolly_instruction_polish.fp16.gguf) | fp16 | 5.56 GB  |
+| [phi-2_dolly_instruction_polish.q2_k.gguf](https://huggingface.co/afrideva/phi-2_dolly_instruction_polish-GGUF/resolve/main/phi-2_dolly_instruction_polish.q2_k.gguf) | q2_k | 1.17 GB  |
+| [phi-2_dolly_instruction_polish.q3_k_m.gguf](https://huggingface.co/afrideva/phi-2_dolly_instruction_polish-GGUF/resolve/main/phi-2_dolly_instruction_polish.q3_k_m.gguf) | q3_k_m | 1.48 GB  |
+| [phi-2_dolly_instruction_polish.q4_k_m.gguf](https://huggingface.co/afrideva/phi-2_dolly_instruction_polish-GGUF/resolve/main/phi-2_dolly_instruction_polish.q4_k_m.gguf) | q4_k_m | 1.79 GB  |
+| [phi-2_dolly_instruction_polish.q5_k_m.gguf](https://huggingface.co/afrideva/phi-2_dolly_instruction_polish-GGUF/resolve/main/phi-2_dolly_instruction_polish.q5_k_m.gguf) | q5_k_m | 2.07 GB  |
+| [phi-2_dolly_instruction_polish.q6_k.gguf](https://huggingface.co/afrideva/phi-2_dolly_instruction_polish-GGUF/resolve/main/phi-2_dolly_instruction_polish.q6_k.gguf) | q6_k | 2.29 GB  |
+| [phi-2_dolly_instruction_polish.q8_0.gguf](https://huggingface.co/afrideva/phi-2_dolly_instruction_polish-GGUF/resolve/main/phi-2_dolly_instruction_polish.q8_0.gguf) | q8_0 | 2.96 GB  |
+## 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. -->
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+# phi-2-sft-out
+This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2813
+## 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: 3e-06
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 4
+### Training results
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| No log        | 0.0   | 1     | 1.7973          |
+| 1.9767        | 0.25  | 5290  | 1.4832          |
+| 1.8474        | 0.5   | 10580 | 1.4356          |
+| 1.8121        | 0.75  | 15870 | 1.4022          |
+| 1.8333        | 1.0   | 21160 | 1.3678          |
+| 1.6601        | 1.25  | 26450 | 1.3508          |
+| 1.5452        | 1.5   | 31740 | 1.3357          |
+| 1.7381        | 1.75  | 37030 | 1.3191          |
+| 1.6256        | 2.0   | 42320 | 1.3090          |
+| 1.5521        | 2.25  | 47610 | 1.2961          |
+| 1.8318        | 2.5   | 52900 | 1.2910          |
+| 1.6761        | 2.75  | 58190 | 1.2901          |
+| 1.6312        | 3.0   | 63480 | 1.2879          |
+| 1.7003        | 3.25  | 68770 | 1.2820          |
+| 1.6915        | 3.5   | 74060 | 1.2814          |
+| 1.5757        | 3.75  | 79350 | 1.2813          |
+### Framework versions
+- Transformers 4.37.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.0
+- Tokenizers 0.15.0
+## Training procedure
+The following `bitsandbytes` quantization config was used during training:
+- quant_method: bitsandbytes
+- load_in_8bit: False
+- load_in_4bit: True
+- llm_int8_threshold: 6.0
+- llm_int8_skip_modules: None
+- llm_int8_enable_fp32_cpu_offload: False
+- llm_int8_has_fp16_weight: False
+- bnb_4bit_quant_type: nf4
+- bnb_4bit_use_double_quant: True
+- bnb_4bit_compute_dtype: bfloat16
+### Framework versions
+- PEFT 0.6.0