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---
language:
- en
license: apache-2.0
datasets:
- OpenAssistant/oasst_top1_2023-08-25
pipeline_tag: text-generation
model-index:
- name: tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1
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: 32.85
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=habanoz/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1
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: 58.16
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=habanoz/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1
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: 25.96
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=habanoz/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1
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: 38.35
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=habanoz/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1
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: 57.7
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=habanoz/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1
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: 0.45
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=habanoz/tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1
name: Open LLM Leaderboard
---
TinyLlama-1.1B-intermediate-step-715k-1.5T finetuned using OpenAssistant/oasst_top1_2023-08-25 dataset.
SFT code:
https://github.com/jzhang38/TinyLlama/tree/main/sft
Evaluation Results at:
https://huggingface.co/datasets/open-llm-leaderboard/details_habanoz__tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1_public/blob/main/results_2023-11-23T17-25-53.937618.json
Command used:
```bash
accelerate launch finetune.py \
--model_name_or_path TinyLlama/TinyLlama-1.1B-intermediate-step-715k-1.5T \
--output_dir ./output/1_5T_FT_lr1e-5_ep5_top1_2023-08-25 \
--logging_steps 10 \
--save_strategy epoch \
--data_seed 42 \
--save_total_limit 2 \
--evaluation_strategy epoch \
--eval_dataset_size 512 \
--max_eval_samples 1000 \
--per_device_eval_batch_size 1 \
--max_new_tokens 32 \
--dataloader_num_workers 3 \
--group_by_length=False \
--logging_strategy steps \
--remove_unused_columns False \
--do_train \
--do_eval \
--warmup_ratio 0.05 \
--lr_scheduler_type constant \
--dataset OpenAssistant/oasst_top1_2023-08-25 \
--dataset_format oasst1 \
--source_max_len 1 \
--target_max_len 1023 \
--per_device_train_batch_size 2 \
--gradient_accumulation_steps 8 \
--max_steps 0 \
--num_train_epochs 5 \
--learning_rate 1e-5 \
--adam_beta2 0.999 \
--max_grad_norm 1.0 \
--weight_decay 0.0 \
--seed 0 \
--trust_remote_code
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_habanoz__tinyllama-oasst1-top1-instruct-full-lr1-5-v0.1)
| Metric |Value|
|---------------------------------|----:|
|Avg. |35.58|
|AI2 Reasoning Challenge (25-Shot)|32.85|
|HellaSwag (10-Shot) |58.16|
|MMLU (5-Shot) |25.96|
|TruthfulQA (0-shot) |38.35|
|Winogrande (5-shot) |57.70|
|GSM8k (5-shot) | 0.45|
|