| PROJECT "RecommenderAI" | |
| DESCRIPTION "Product recommendation engine for e-commerce and content platforms" | |
| DATASET { | |
| train: "dataset/user_behavior.csv" | |
| format: "csv" | |
| type: "regression" | |
| } | |
| MODEL { | |
| base: "oktoseek/recommender-base" | |
| architecture: "transformer" | |
| parameters: 80M | |
| context_window: 512 | |
| } | |
| TRAIN { | |
| epochs: 10 | |
| batch_size: 128 | |
| learning_rate: 0.0005 | |
| optimizer: "adamw" | |
| scheduler: "linear" | |
| device: "cuda" | |
| gradient_accumulation: 4 | |
| } | |
| METRICS { | |
| f1 | |
| accuracy | |
| cosine_similarity | |
| mae | |
| } | |
| EXPORT { | |
| format: ["okm", "onnx"] | |
| path: "export/" | |
| } | |
| DEPLOY { | |
| target: "api" | |
| endpoint: "http://localhost:9000/recommend" | |
| requires_auth: true | |
| } | |