README.md

---
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|