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---
license: apache-2.0
---
**Note: internal model, not ready for use**
This is an intermediate model used as base-model for further pythia 12b SFT-8 experiments.
It was trained on a wider set of instruction-tuning datasets for >12.5k steps with batch-size 128 and a context size of 2048.
The gpt4all dataset had "as a language model" *contamination* (>1.8k entries). We added filtering later, but this model (pre-v8) was trained on the raw unfildered gpt4all dataset.
- wandb: https://wandb.ai/open-assistant/supervised-finetuning/runs/sytsyhrp
- [sampling report](https://open-assistant.github.io/oasst-model-eval/?f=https%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2Fmain%2Fsampling_reports%2Foasst-pretrained%2F2023-05-05_OpenAssistant_pythia-12b-pre-v8-12_5k-steps_sampling_noprefix2.json)
Datasets:
```
pretrain:
num_train_epochs: 1
weight_decay: 0.0
use_custom_sampler: true
sort_by_length: false
datasets:
- gpteacher_roleplay:
val_split: 0.05
- red_pajama:
fraction: 0.25
max_val_set: 1000
- wizardlm_70k:
val_split: 0.05
max_val_set: 500
- joke:
val_split: 0.05
- poem_instructions:
val_split: 0.025
- oa_stackexchange:
val_split: 0.05
fraction: 0.1
max_val_set: 1000
- tell_a_joke:
val_split: 0.05
max_val_set: 250
- webgpt:
val_split: 0.05
max_val_set: 250
- gpt4all:
val_split: 0.01
max_val_set: 1000
- alpaca_gpt4:
val_split: 0.025
max_val_set: 250
- code_alpaca:
val_split: 0.05
max_val_set: 250
- vicuna:
max_val_set: 250
- oig_file:
source_url: https://huggingface.co/datasets/laion/OIG/resolve/main/unified_chip2.jsonl
max_count: 10000
min_length: 250
val_split: 0.05
max_val_set: 250
- minimath:
val_split: 0.05
- humaneval_mbpp_codegen_qa:
val_split: 0.05
- humaneval_mbpp_testgen_qa:
val_split: 0.05
- grade_school_math_instructions:
val_split: 0.05
- recipes:
val_split: 0.05
- cmu_wiki_qa:
val_split: 0.05
- oa_wiki_qa_bart_10000row:
val_split: 0.05
max_val_set: 250
- prosocial_dialogue:
fraction: 0.1
max_val_set: 250
- explain_prosocial:
fraction: 0.075
max_val_set: 250
- soda:
fraction: 0.25
max_val_set: 1000
- oa_leet10k:
val_split: 0.05
max_val_set: 250
- dolly15k:
val_split: 0.05
max_val_set: 300
```
Pythia:
```
pythia-12b-pretrain:
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: 4
per_device_train_batch_size: 4
per_device_eval_batch_size: 4
eval_steps: 251
save_steps: 500
num_train_epochs: 1
save_total_limit: 2
deepspeed_config: configs/zero_config_pretrain.json
```
Command used: `deepspeed trainer_sft.py --show_dataset_stats --configs defaults pythia-12b-pretrain pretrain --cache_dir .cache/ --output_dir .saved/pythia-12b-super-pretrain2 --deepspeed`

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"_name_or_path": ".saved/pythia-12b-super-pretrain2/",
"architectures": [
"GPTNeoXForCausalLM"
],
"bos_token_id": 0,
"eos_token_id": 0,
"hidden_act": "gelu",
"hidden_size": 5120,
"initializer_range": 0.02,
"intermediate_size": 20480,
"layer_norm_eps": 1e-05,
"max_position_embeddings": 2048,
"model_type": "gpt_neox",
"num_attention_heads": 40,
"num_hidden_layers": 36,
"rotary_emb_base": 10000,
"rotary_pct": 0.25,
"tie_word_embeddings": false,
"torch_dtype": "float16",
"transformers_version": "4.28.0.dev0",
"use_cache": true,
"use_parallel_residual": true,
"vocab_size": 50288
}

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}

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special_tokens_map.json Normal file
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{
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}

100574
tokenizer.json Normal file
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10
tokenizer_config.json Normal file
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{
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