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--- |
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license: other |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: microsoft/phi-2 |
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model-index: |
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- name: phi-2-sft-out |
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results: [] |
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--- |
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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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[<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) |
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# phi-2-sft-out |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2813 |
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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: 3e-06 |
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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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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| No log | 0.0 | 1 | 1.7973 | |
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| 1.9767 | 0.25 | 5290 | 1.4832 | |
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| 1.8474 | 0.5 | 10580 | 1.4356 | |
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| 1.8121 | 0.75 | 15870 | 1.4022 | |
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| 1.8333 | 1.0 | 21160 | 1.3678 | |
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| 1.6601 | 1.25 | 26450 | 1.3508 | |
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| 1.5452 | 1.5 | 31740 | 1.3357 | |
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| 1.7381 | 1.75 | 37030 | 1.3191 | |
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| 1.6256 | 2.0 | 42320 | 1.3090 | |
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| 1.5521 | 2.25 | 47610 | 1.2961 | |
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| 1.8318 | 2.5 | 52900 | 1.2910 | |
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| 1.6761 | 2.75 | 58190 | 1.2901 | |
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| 1.6312 | 3.0 | 63480 | 1.2879 | |
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| 1.7003 | 3.25 | 68770 | 1.2820 | |
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| 1.6915 | 3.5 | 74060 | 1.2814 | |
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| 1.5757 | 3.75 | 79350 | 1.2813 | |
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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 2.16.0 |
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- Tokenizers 0.15.0 |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: bitsandbytes |
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- load_in_8bit: False |
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- load_in_4bit: True |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: nf4 |
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- bnb_4bit_use_double_quant: True |
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- bnb_4bit_compute_dtype: bfloat16 |
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### Framework versions |
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- PEFT 0.6.0 |
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