GPT-NeoX trained on MiniPile, for a baseline to compare my MANN models against. Uses NeelNanda/gpt-neox-tokenizer-digits for tokenization.
The exact model configuration is as follows:
cfg = GPTNeoXConfig(
vocab_size = len(tokenizer),
hidden_size = 768,
intermediate_size = 768*4,
num_hidden_layers = 12,
num_attention_heads = 12,
tie_word_embeddings = True,
hidden_act = "gelu_new",
tokenizer = "NeelNanda/gpt-neox-tokenizer-digits"
)
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 25.1 |
| ARC (25-shot) | 20.73 |
| HellaSwag (10-shot) | 27.03 |
| MMLU (5-shot) | 25.31 |
| TruthfulQA (0-shot) | 49.19 |
| Winogrande (5-shot) | 52.33 |
| GSM8K (5-shot) | 0.0 |
| DROP (3-shot) | 1.09 |
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