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phi-2_dolly_instruction_polish-GGUF
afrideva/phi-2_dolly_instruction_polish-GGUF
phi-2_dolly_instruction_polish-GGUF is a text generation model from afrideva. Use it when you need the model to write or continue text. It is set up for peft. The card lists the license as other.
Quantized GGUF model files for phi-2dollyinstructionpolish from s3nh
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Repo size
17.3 GB
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.gguf17.3 GB · 100%
At a glance
- Task
- Text Generation
- Library
- peft
- License
- other
- Access
- Public
- Created
- Dec 24, 2023
- Updated
- Dec 24, 2023
- SHA
- 923ff1df
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Base models
Model card
From the Hugging Face model README
s3nh/phi-2_dolly_instruction_polish-GGUF
Quantized GGUF model files for phi-2_dolly_instruction_polish from s3nh
| Name | Quant method | Size |
|---|---|---|
| phi-2_dolly_instruction_polish.fp16.gguf | fp16 | 5.56 GB |
| phi-2_dolly_instruction_polish.q2_k.gguf | q2_k | 1.17 GB |
| phi-2_dolly_instruction_polish.q3_k_m.gguf | q3_k_m | 1.48 GB |
| phi-2_dolly_instruction_polish.q4_k_m.gguf | q4_k_m | 1.79 GB |
| phi-2_dolly_instruction_polish.q5_k_m.gguf | q5_k_m | 2.07 GB |
| phi-2_dolly_instruction_polish.q6_k.gguf | q6_k | 2.29 GB |
| 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. -->phi-2-sft-out
This model is a fine-tuned version of 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
- Task
- Text Generation
- Library
- peft
- License
- other
- Created
- Dec 24, 2023
- Updated
- Dec 24, 2023