--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task3_fold0 results: [] --- # arabert_cross_relevance_task3_fold0 This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2395 - Qwk: 0.2008 - Mse: 0.2396 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | No log | 0.125 | 2 | 0.6036 | 0.0322 | 0.6039 | | No log | 0.25 | 4 | 0.2956 | 0.1240 | 0.2957 | | No log | 0.375 | 6 | 0.2567 | 0.1067 | 0.2568 | | No log | 0.5 | 8 | 0.2551 | 0.0962 | 0.2553 | | No log | 0.625 | 10 | 0.2302 | 0.0791 | 0.2304 | | No log | 0.75 | 12 | 0.2219 | 0.1048 | 0.2221 | | No log | 0.875 | 14 | 0.2288 | 0.1179 | 0.2291 | | No log | 1.0 | 16 | 0.2285 | 0.1629 | 0.2287 | | No log | 1.125 | 18 | 0.2532 | 0.2761 | 0.2534 | | No log | 1.25 | 20 | 0.2397 | 0.2284 | 0.2399 | | No log | 1.375 | 22 | 0.2317 | 0.1215 | 0.2320 | | No log | 1.5 | 24 | 0.2340 | 0.1485 | 0.2342 | | No log | 1.625 | 26 | 0.2412 | 0.2448 | 0.2414 | | No log | 1.75 | 28 | 0.2819 | 0.2575 | 0.2820 | | No log | 1.875 | 30 | 0.2502 | 0.2245 | 0.2503 | | No log | 2.0 | 32 | 0.2449 | 0.2115 | 0.2452 | | No log | 2.125 | 34 | 0.2459 | 0.2412 | 0.2461 | | No log | 2.25 | 36 | 0.2526 | 0.2570 | 0.2528 | | No log | 2.375 | 38 | 0.2460 | 0.2406 | 0.2462 | | No log | 2.5 | 40 | 0.2535 | 0.2576 | 0.2536 | | No log | 2.625 | 42 | 0.2448 | 0.1981 | 0.2449 | | No log | 2.75 | 44 | 0.2294 | 0.2076 | 0.2296 | | No log | 2.875 | 46 | 0.2305 | 0.2211 | 0.2306 | | No log | 3.0 | 48 | 0.2436 | 0.3108 | 0.2438 | | No log | 3.125 | 50 | 0.2515 | 0.2985 | 0.2516 | | No log | 3.25 | 52 | 0.2389 | 0.2228 | 0.2391 | | No log | 3.375 | 54 | 0.2444 | 0.2286 | 0.2445 | | No log | 3.5 | 56 | 0.2431 | 0.1981 | 0.2433 | | No log | 3.625 | 58 | 0.2417 | 0.1722 | 0.2418 | | No log | 3.75 | 60 | 0.2397 | 0.1740 | 0.2398 | | No log | 3.875 | 62 | 0.2456 | 0.1383 | 0.2457 | | No log | 4.0 | 64 | 0.2512 | 0.1025 | 0.2513 | | No log | 4.125 | 66 | 0.2350 | 0.1347 | 0.2351 | | No log | 4.25 | 68 | 0.2301 | 0.2110 | 0.2302 | | No log | 4.375 | 70 | 0.2327 | 0.2653 | 0.2328 | | No log | 4.5 | 72 | 0.2250 | 0.2641 | 0.2252 | | No log | 4.625 | 74 | 0.2301 | 0.2694 | 0.2303 | | No log | 4.75 | 76 | 0.2409 | 0.3036 | 0.2411 | | No log | 4.875 | 78 | 0.2453 | 0.2611 | 0.2454 | | No log | 5.0 | 80 | 0.2448 | 0.2241 | 0.2450 | | No log | 5.125 | 82 | 0.2464 | 0.1904 | 0.2466 | | No log | 5.25 | 84 | 0.2462 | 0.1493 | 0.2465 | | No log | 5.375 | 86 | 0.2336 | 0.1137 | 0.2338 | | No log | 5.5 | 88 | 0.2304 | 0.1648 | 0.2306 | | No log | 5.625 | 90 | 0.2297 | 0.1804 | 0.2298 | | No log | 5.75 | 92 | 0.2240 | 0.1481 | 0.2242 | | No log | 5.875 | 94 | 0.2360 | 0.1350 | 0.2362 | | No log | 6.0 | 96 | 0.2435 | 0.1401 | 0.2438 | | No log | 6.125 | 98 | 0.2332 | 0.1773 | 0.2334 | | No log | 6.25 | 100 | 0.2361 | 0.1842 | 0.2363 | | No log | 6.375 | 102 | 0.2427 | 0.1902 | 0.2429 | | No log | 6.5 | 104 | 0.2452 | 0.2024 | 0.2454 | | No log | 6.625 | 106 | 0.2452 | 0.1985 | 0.2454 | | No log | 6.75 | 108 | 0.2439 | 0.2049 | 0.2441 | | No log | 6.875 | 110 | 0.2397 | 0.2015 | 0.2399 | | No log | 7.0 | 112 | 0.2346 | 0.2150 | 0.2347 | | No log | 7.125 | 114 | 0.2303 | 0.2182 | 0.2304 | | No log | 7.25 | 116 | 0.2253 | 0.2061 | 0.2254 | | No log | 7.375 | 118 | 0.2231 | 0.2023 | 0.2232 | | No log | 7.5 | 120 | 0.2230 | 0.1999 | 0.2231 | | No log | 7.625 | 122 | 0.2268 | 0.2027 | 0.2270 | | No log | 7.75 | 124 | 0.2309 | 0.2117 | 0.2310 | | No log | 7.875 | 126 | 0.2333 | 0.2069 | 0.2334 | | No log | 8.0 | 128 | 0.2363 | 0.2151 | 0.2364 | | No log | 8.125 | 130 | 0.2387 | 0.2141 | 0.2389 | | No log | 8.25 | 132 | 0.2410 | 0.2151 | 0.2412 | | No log | 8.375 | 134 | 0.2430 | 0.1999 | 0.2432 | | No log | 8.5 | 136 | 0.2449 | 0.1974 | 0.2450 | | No log | 8.625 | 138 | 0.2463 | 0.1906 | 0.2465 | | No log | 8.75 | 140 | 0.2479 | 0.1963 | 0.2480 | | No log | 8.875 | 142 | 0.2460 | 0.2045 | 0.2462 | | No log | 9.0 | 144 | 0.2447 | 0.2161 | 0.2448 | | No log | 9.125 | 146 | 0.2444 | 0.2145 | 0.2446 | | No log | 9.25 | 148 | 0.2431 | 0.2145 | 0.2432 | | No log | 9.375 | 150 | 0.2414 | 0.2036 | 0.2416 | | No log | 9.5 | 152 | 0.2400 | 0.2000 | 0.2401 | | No log | 9.625 | 154 | 0.2390 | 0.2044 | 0.2392 | | No log | 9.75 | 156 | 0.2391 | 0.2044 | 0.2392 | | No log | 9.875 | 158 | 0.2394 | 0.2008 | 0.2395 | | No log | 10.0 | 160 | 0.2395 | 0.2008 | 0.2396 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1