Stuti Agarwal
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End of training
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README.md
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---
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license: mit
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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: TheBloke/zephyr-7B-alpha-GPTQ
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model-index:
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- name: zephyr-chatbot
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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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# zephyr-chatbot
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This model is a fine-tuned version of [TheBloke/zephyr-7B-alpha-GPTQ](https://huggingface.co/TheBloke/zephyr-7B-alpha-GPTQ) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8794
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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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The following `bitsandbytes` quantization config was used during training:
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- quant_method: gptq
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- bits: 4
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- tokenizer: None
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- dataset: None
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- group_size: 128
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- damp_percent: 0.1
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- desc_act: True
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- sym: True
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- true_sequential: True
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- use_cuda_fp16: False
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- model_seqlen: 4095
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- block_name_to_quantize: model.layers
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- module_name_preceding_first_block: ['model.embed_tokens']
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- batch_size: 1
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- pad_token_id: None
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- use_exllama: False
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- max_input_length: None
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- exllama_config: {'version': <ExllamaVersion.ONE: 1>}
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- cache_block_outputs: True
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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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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- training_steps: 1000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.9364 | 1.0 | 121 | 0.9402 |
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| 0.8289 | 2.0 | 242 | 0.8849 |
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| 0.7249 | 3.0 | 363 | 0.8540 |
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| 0.6322 | 4.0 | 484 | 0.8387 |
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| 0.5337 | 5.0 | 605 | 0.8475 |
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| 0.4523 | 6.0 | 726 | 0.8586 |
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| 0.405 | 7.0 | 847 | 0.8698 |
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| 0.3965 | 8.0 | 968 | 0.8794 |
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| 0.3859 | 8.26 | 1000 | 0.8794 |
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### Framework versions
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- PEFT 0.7.0
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- Transformers 4.36.0.dev0
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- Pytorch 2.1.1+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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adapter_model.safetensors
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emissions.csv
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timestamp,project_name,run_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
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2023-12-10T23:58:16,codecarbon,463d7c05-7786-4d02-a093-f13933f14fc2,12112.945874452591,0.32955738331212314,2.72070383809105e-05,42.5,128.371,73.71764945983887,0.14299199634525528,0.5018511333381926,0.2479411869527795,0.8927843166362271,United States,USA,virginia,,,Linux-5.15.0-67-generic-x86_64-with-glibc2.29,3.8.10,2.2.3,30,Intel(R) Xeon(R) Platinum 8358 CPU @ 2.60GHz,1,1 x NVIDIA A10,-77.539,39.018,196.5803985595703,machine,N,1.0
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runs/Dec10_20-36-19_141-148-31-151/events.out.tfevents.1702240581.141-148-31-151.310144.0
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