metadata
language:
- en
license: apache-2.0
tags:
- sft
pipeline_tag: text-generation
widget:
- text: >-
<|prompter|>What is a meme, and what's the history behind this
word?<|endoftext|><|assistant|>
- text: <|prompter|>What's the Earth total population<|endoftext|><|assistant|>
- text: >-
<|prompter|>Write a story about future of AI
development<|endoftext|><|assistant|>
model-index:
- name: oasst-sft-4-pythia-12b-epoch-3.5
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 45.73
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 68.59
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 26.82
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 37.81
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 65.9
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 3.03
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5
name: Open LLM Leaderboard
Open-Assistant SFT-4 12B Model
This is the 4th iteration English supervised-fine-tuning (SFT) model of the Open-Assistant project. It is based on a Pythia 12B that was fine-tuned on human demonstrations of assistant conversations collected through the https://open-assistant.io/ human feedback web app before March 25, 2023.
Model Details
- Developed by: Open-Assistant Contributors
- Model type: Transformer-based Language Model
- Language: English
- Finetuned from: EleutherAI / pythia-12b-deduped
- Code: Open-Assistant/model/model_training
- Demo: Continuations for 250 random prompts
- License: Apache 2.0
- Contact: Open-Assistant Discord
Prompting
Two special tokens are used to mark the beginning of user and assistant turns:
<|prompter|> and <|assistant|>. Each turn ends with a <|endoftext|> token.
Input prompt example:
<|prompter|>What is a meme, and what's the history behind this word?<|endoftext|><|assistant|>
The input ends with the <|assistant|> token to signal that the model should
start generating the assistant reply.
Dev Details
- wandb: https://wandb.ai/open-assistant/supervised-finetuning/runs/770a0t41
- base model: andreaskoepf/pythia-12b-pre-2000
- checkpoint: 4000 steps
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
data:
reference-data:
datasets:
- oasst_export:
lang: "bg,ca,cs,da,de,en,es,fr,hr,hu,it,nl,pl,pt,ro,ru,sl,sr,sv,uk"
input_file_path: 2023-03-25_oasst_research_ready_synth_labels.jsonl.gz
val_split: 0.05
- alpaca
sort_by_length: false
use_custom_sampler: false
pythia:
reference-pythia-12b:
dtype: fp16
log_dir: "pythia_log_12b"
learning_rate: 6e-6
model_name: EleutherAI/pythia-12b-deduped
output_dir: pythia_model_12b
weight_decay: 0.0
max_length: 2048
warmup_steps: 100
gradient_checkpointing: true
gradient_accumulation_steps: 2
per_device_train_batch_size: 4
per_device_eval_batch_size: 4
eval_steps: 100
save_steps: 1000
num_train_epochs: 8
save_total_limit: 4
zero config:
{
"fp16": {
"enabled": "auto",
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 16,
"hysteresis": 2,
"min_loss_scale": 1
},
"bf16": {
"enabled": "auto"
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": "auto",
"betas": "auto",
"eps": "auto",
"weight_decay": "auto"
}
},
"scheduler": {
"type": "WarmupDecayLR",
"params": {
"warmup_min_lr": "auto",
"warmup_max_lr": "auto",
"warmup_num_steps": "auto",
"total_num_steps": "auto"
}
},
"zero_optimization": {
"stage": 2,
"allgather_partitions": true,
"allgather_bucket_size": 1e9,
"overlap_comm": false,
"reduce_scatter": true,
"reduce_bucket_size": 1e9,
"contiguous_gradients": true
},
"gradient_accumulation_steps": "auto",
"gradient_clipping": "auto",
"steps_per_print": 2000,
"train_batch_size": "auto",
"train_micro_batch_size_per_gpu": "auto",
"wall_clock_breakdown": false
}
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 41.31 |
| AI2 Reasoning Challenge (25-Shot) | 45.73 |
| HellaSwag (10-Shot) | 68.59 |
| MMLU (5-Shot) | 26.82 |
| TruthfulQA (0-shot) | 37.81 |
| Winogrande (5-shot) | 65.90 |
| GSM8k (5-shot) | 3.03 |