139 lines
4.4 KiB
Markdown
139 lines
4.4 KiB
Markdown
---
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license: apache-2.0
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language:
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- en
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tags:
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- sft
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pipeline_tag: text-generation
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widget:
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- text: <|prompter|>What is a meme, and what's the history behind this word?<|endoftext|><|assistant|>
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- text: <|prompter|>What's the Earth total population<|endoftext|><|assistant|>
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- text: <|prompter|>Write a story about future of AI development<|endoftext|><|assistant|>
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---
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# Open-Assistant SFT-4 12B Model
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This is the 4th iteration English supervised-fine-tuning (SFT) model of
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the [Open-Assistant](https://github.com/LAION-AI/Open-Assistant) project.
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It is based on a Pythia 12B that was fine-tuned on human demonstrations
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of assistant conversations collected through the
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[https://open-assistant.io/](https://open-assistant.io/) human feedback web
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app before March 25, 2023.
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## Model Details
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- **Developed by:** [Open-Assistant Contributors](https://open-assistant.io/)
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- **Model type:** Transformer-based Language Model
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- **Language:** English
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- **Finetuned from:** [EleutherAI / pythia-12b-deduped](https://huggingface.co/EleutherAI/pythia-12b-deduped)
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- **Code:** [Open-Assistant/model/model_training](https://github.com/LAION-AI/Open-Assistant/tree/main/model/model_training)
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- **Demo:** [Continuations for 250 random prompts](https://open-assistant.github.io/oasst-model-eval/?f=https%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2Fmain%2Fsampling_reports%2Foasst-sft%2F2023-04-03_andreaskoepf_oasst-sft-4-pythia-12b-epoch-3_5_sampling_noprefix_lottery.json%0Ahttps%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2Fmain%2Fsampling_reports%2Fchat-gpt%2F2023-04-11_gpt-3.5-turbo_lottery.json)
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- **License:** Apache 2.0
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- **Contact:** [Open-Assistant Discord](https://ykilcher.com/open-assistant-discord)
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## Prompting
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Two special tokens are used to mark the beginning of user and assistant turns:
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`<|prompter|>` and `<|assistant|>`. Each turn ends with a `<|endoftext|>` token.
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Input prompt example:
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```
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<|prompter|>What is a meme, and what's the history behind this word?<|endoftext|><|assistant|>
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```
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The input ends with the `<|assistant|>` token to signal that the model should
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start generating the assistant reply.
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## Dev Details
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- wandb: https://wandb.ai/open-assistant/supervised-finetuning/runs/770a0t41
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- base model: [andreaskoepf/pythia-12b-pre-2000](https://huggingface.co/andreaskoepf/pythia-12b-pre-2000)
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- checkpoint: 4000 steps
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command: `deepspeed trainer_sft.py --configs defaults reference-data reference-pythia-12b --cache_dir /home/ubuntu/data_cache --output_dir .saved/oasst-sft-3-pythia-12b-reference_2kpre --num_train_epochs 8 --residual_dropout 0.2 --deepspeed --use_flash_attention true --model_name andreaskoepf/pythia-12b-pre-2000`
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data:
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```
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reference-data:
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datasets:
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- oasst_export:
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lang: "bg,ca,cs,da,de,en,es,fr,hr,hu,it,nl,pl,pt,ro,ru,sl,sr,sv,uk"
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input_file_path: 2023-03-25_oasst_research_ready_synth_labels.jsonl.gz
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val_split: 0.05
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- alpaca
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sort_by_length: false
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use_custom_sampler: false
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```
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pythia:
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```
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reference-pythia-12b:
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dtype: fp16
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log_dir: "pythia_log_12b"
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learning_rate: 6e-6
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model_name: EleutherAI/pythia-12b-deduped
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output_dir: pythia_model_12b
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weight_decay: 0.0
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max_length: 2048
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warmup_steps: 100
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gradient_checkpointing: true
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gradient_accumulation_steps: 2
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per_device_train_batch_size: 4
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per_device_eval_batch_size: 4
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eval_steps: 100
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save_steps: 1000
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num_train_epochs: 8
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save_total_limit: 4
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```
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zero config:
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```
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{
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"fp16": {
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"enabled": "auto",
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"loss_scale": 0,
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"loss_scale_window": 1000,
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"initial_scale_power": 16,
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"hysteresis": 2,
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"min_loss_scale": 1
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},
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"bf16": {
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"enabled": "auto"
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},
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"optimizer": {
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"type": "AdamW",
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"params": {
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"lr": "auto",
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"betas": "auto",
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"eps": "auto",
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"weight_decay": "auto"
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}
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},
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"scheduler": {
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"type": "WarmupDecayLR",
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"params": {
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"warmup_min_lr": "auto",
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"warmup_max_lr": "auto",
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"warmup_num_steps": "auto",
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"total_num_steps": "auto"
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}
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},
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"zero_optimization": {
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"stage": 2,
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"allgather_partitions": true,
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"allgather_bucket_size": 1e9,
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"overlap_comm": false,
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"reduce_scatter": true,
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"reduce_bucket_size": 1e9,
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"contiguous_gradients": true
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},
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"gradient_accumulation_steps": "auto",
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"gradient_clipping": "auto",
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"steps_per_print": 2000,
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"train_batch_size": "auto",
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"train_micro_batch_size_per_gpu": "auto",
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"wall_clock_breakdown": false
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}
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``` |