BraylonDash
commited on
Model save
Browse files- README.md +62 -0
- adapter_model.safetensors +1 -1
- all_results.json +8 -0
- emissions.csv +2 -0
- runs/Sep28_21-39-26_gpu4-119-5/events.out.tfevents.1727523614.gpu4-119-5.12283.0 +2 -2
- train_results.json +8 -0
- trainer_state.json +2718 -0
README.md
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---
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license: apache-2.0
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library_name: peft
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tags:
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- trl
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- dpo
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- generated_from_trainer
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base_model: DUAL-GPO/phi-2-sft-lora-ultrachat-merged
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model-index:
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- name: phi-2-kto-i0
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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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# phi-2-kto-i0
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This model is a fine-tuned version of [DUAL-GPO/phi-2-sft-lora-ultrachat-merged](https://huggingface.co/DUAL-GPO/phi-2-sft-lora-ultrachat-merged) on the None dataset.
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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: 5e-06
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- total_eval_batch_size: 8
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1
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### Training results
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### Framework versions
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- PEFT 0.7.1
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- Transformers 4.36.2
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- Pytorch 2.1.2
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- Datasets 2.14.6
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- Tokenizers 0.15.2
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 335579632
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version https://git-lfs.github.com/spec/v1
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oid sha256:0b481bae16a28ec9c1d5d85715b5a5373bcf2ceda3ead20d169ccf6d23ef0a42
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size 335579632
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all_results.json
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{
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"epoch": 1.0,
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"train_loss": 0.09940854217369519,
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"train_runtime": 5146.4957,
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"train_samples": 61135,
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"train_samples_per_second": 11.879,
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"train_steps_per_second": 0.371
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}
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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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2024-09-28T23:06:01,codecarbon,4ad68e38-f708-4965-8116-4cc9c3bca396,5146.503284215927,0.0029854159599475927,5.800862828755433e-07,42.5,519.923,188.74309015274048,0.0607566486707992,0.9262474175948083,0.2688400132142028,1.2558440794798107,Canada,CAN,quebec,,,Linux-5.15.0-84-generic-x86_64-with-glibc2.35,3.10.14,2.2.3,32,Intel(R) Xeon(R) W-3335 CPU @ 3.40GHz,4,4 x NVIDIA GeForce RTX 4090,-71.2,46.8,503.3149070739746,machine,N,1.0
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runs/Sep28_21-39-26_gpu4-119-5/events.out.tfevents.1727523614.gpu4-119-5.12283.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:aa5134d16c0b02dfad1fc80ca244c33555c4fb3dc31bec86ad9eb2901146c89e
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size 31226
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train_results.json
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{
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"epoch": 1.0,
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"train_loss": 0.09940854217369519,
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"train_runtime": 5146.4957,
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"train_samples": 61135,
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"train_samples_per_second": 11.879,
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"train_steps_per_second": 0.371
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}
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trainer_state.json
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