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---
license: apache-2.0
datasets:
- euclaise/SuperMC
- euclaise/prm800k_preferences
model-index:
- name: crow-1b
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: 25.51
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=euclaise/crow-1b
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: 25.87
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=euclaise/crow-1b
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: 24.8
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=euclaise/crow-1b
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: 48.28
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=euclaise/crow-1b
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: 49.41
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=euclaise/crow-1b
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: 0.83
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=euclaise/crow-1b
name: Open LLM Leaderboard
---
Expirements in large-scale small-scale preference learning.
**This one was a failure, it benchmarks horribly, despite responding okay to trivia questions in testing**
falcon-rw-1b trained with PRO (preference ranking optimization, see https://arxiv.org/abs/2306.17492) on SuperMC and PRM800K (only stage 1) for 3 epochs, using my supertrainer2000 framework.
This is an expiremental model.
Benchmarks coming soon.
Hyperparameters:
- AdamW, weight decay of 0.01, otherwise default hyperparams
- Maximum LR of 1e-5
- Cosine schedule with a warmup of 5400 steps
- Batch size of 4 (2 real x 2 accumulated)
- Maximum of 5 epochs, early stopping (visual observation), stopped after 3
- Gradient clipping norm value of 1.0
- PRO beta of 4
Training prompt format:
```
### Query
[insert instruction here]
### Answer
[insert response here]
```
# [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_euclaise__crow-1b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |29.12|
|AI2 Reasoning Challenge (25-Shot)|25.51|
|HellaSwag (10-Shot) |25.87|
|MMLU (5-Shot) |24.80|
|TruthfulQA (0-shot) |48.28|
|Winogrande (5-shot) |49.41|
|GSM8k (5-shot) | 0.83|
|