Instructions to use danielfein/raid-ce-gemma4-e4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielfein/raid-ce-gemma4-e4b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("danielfein/raid-ce-gemma4-e4b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add seed 42 evaluation
Browse files- seeds/42/summary.json +29 -0
seeds/42/summary.json
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"ai_token": "/workspace/expanded_raid_ai_20260726/outputs/gemma_ai_pairwise_finecurve5k_lr1e4_seed42/full/step_00075/tokens/ai_token.pt",
|
| 3 |
+
"beemo": {
|
| 4 |
+
"accuracy_at_zero": 0.7059639389736477,
|
| 5 |
+
"auroc": 0.754864147563069,
|
| 6 |
+
"auroc_ci95": [
|
| 7 |
+
0.7407155051042317,
|
| 8 |
+
0.7685814134621077
|
| 9 |
+
],
|
| 10 |
+
"mean_ai_score": 8.748883680532197,
|
| 11 |
+
"mean_human_score": 0.3008289260551216,
|
| 12 |
+
"pairs": 2163,
|
| 13 |
+
"texts": 4326
|
| 14 |
+
},
|
| 15 |
+
"eval_only": true,
|
| 16 |
+
"human_token": "/workspace/rebuttal_apo_20260724/outputs/rebuttal_text_multiseed_20260726/host_b_complete/gemma4_human_steps900_20260726/tokens/human_token.pt",
|
| 17 |
+
"raid_standard_test": {
|
| 18 |
+
"accuracy_at_zero": 0.848,
|
| 19 |
+
"auroc": 0.9641748888888888,
|
| 20 |
+
"auroc_ci95": [
|
| 21 |
+
0.9597294527777779,
|
| 22 |
+
0.9685374472222222
|
| 23 |
+
],
|
| 24 |
+
"mean_ai_score": 6.8369182267834745,
|
| 25 |
+
"mean_human_score": -12.562866653303304,
|
| 26 |
+
"pairs": 3000,
|
| 27 |
+
"texts": 6000
|
| 28 |
+
}
|
| 29 |
+
}
|