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meeting-sensai-2

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+ ---
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: meeting-sensai-2
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # meeting-sensai-2
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+
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+ This model is a fine-tuned version of [raquelclemente/meeting-sensai](https://huggingface.co/raquelclemente/meeting-sensai) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.7555
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+ - Rouge1: 0.3039
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+ - Rouge2: 0.1453
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+ - Rougel: 0.2534
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+ - Rougelsum: 0.2529
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0005
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 32
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 5
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+ - num_epochs: 4
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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+ | No log | 0.09 | 30 | 3.1865 | 0.1936 | 0.0509 | 0.1606 | 0.1611 |
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+ | No log | 0.18 | 60 | 2.9928 | 0.2636 | 0.0961 | 0.1951 | 0.1969 |
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+ | No log | 0.28 | 90 | 2.9472 | 0.2667 | 0.0921 | 0.2097 | 0.2115 |
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+ | No log | 0.37 | 120 | 2.8506 | 0.2755 | 0.1151 | 0.2243 | 0.2243 |
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+ | No log | 0.46 | 150 | 2.8883 | 0.2505 | 0.1134 | 0.2057 | 0.2056 |
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+ | No log | 0.55 | 180 | 2.8464 | 0.2946 | 0.1229 | 0.2449 | 0.2446 |
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+ | No log | 0.65 | 210 | 2.8274 | 0.2668 | 0.1005 | 0.2112 | 0.2120 |
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+ | No log | 0.74 | 240 | 2.8153 | 0.2960 | 0.1268 | 0.2392 | 0.2384 |
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+ | No log | 0.83 | 270 | 2.7803 | 0.2940 | 0.1203 | 0.2323 | 0.2312 |
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+ | No log | 0.92 | 300 | 2.8129 | 0.2966 | 0.1083 | 0.2447 | 0.2444 |
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+ | No log | 1.02 | 330 | 2.7478 | 0.2977 | 0.1152 | 0.2388 | 0.2382 |
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+ | No log | 1.11 | 360 | 2.7482 | 0.2905 | 0.1135 | 0.2379 | 0.2369 |
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+ | No log | 1.2 | 390 | 2.7646 | 0.3215 | 0.1260 | 0.2590 | 0.2594 |
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+ | No log | 1.29 | 420 | 2.7763 | 0.3164 | 0.1273 | 0.2536 | 0.2524 |
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+ | No log | 1.38 | 450 | 2.8300 | 0.2867 | 0.1198 | 0.2182 | 0.2186 |
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+ | No log | 1.48 | 480 | 2.7683 | 0.3313 | 0.1567 | 0.2647 | 0.2643 |
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+ | 2.7437 | 1.57 | 510 | 2.7669 | 0.3004 | 0.1313 | 0.2545 | 0.2541 |
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+ | 2.7437 | 1.66 | 540 | 2.7242 | 0.2960 | 0.1394 | 0.2404 | 0.2409 |
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+ | 2.7437 | 1.75 | 570 | 2.7565 | 0.3042 | 0.1172 | 0.2475 | 0.2463 |
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+ | 2.7437 | 1.85 | 600 | 2.7866 | 0.2994 | 0.1300 | 0.2375 | 0.2373 |
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+ | 2.7437 | 1.94 | 630 | 2.7293 | 0.3122 | 0.1306 | 0.2611 | 0.2581 |
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+ | 2.7437 | 2.03 | 660 | 2.7398 | 0.3194 | 0.1314 | 0.2504 | 0.2506 |
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+ | 2.7437 | 2.12 | 690 | 2.7183 | 0.3109 | 0.1374 | 0.2591 | 0.2588 |
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+ | 2.7437 | 2.22 | 720 | 2.7929 | 0.3184 | 0.1454 | 0.2562 | 0.2562 |
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+ | 2.7437 | 2.31 | 750 | 2.8156 | 0.3360 | 0.1566 | 0.2613 | 0.2611 |
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+ | 2.7437 | 2.4 | 780 | 2.7750 | 0.3125 | 0.1364 | 0.2496 | 0.2494 |
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+ | 2.7437 | 2.49 | 810 | 2.8071 | 0.2928 | 0.1434 | 0.2501 | 0.2491 |
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+ | 2.7437 | 2.58 | 840 | 2.7322 | 0.3043 | 0.1403 | 0.2488 | 0.2484 |
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+ | 2.7437 | 2.68 | 870 | 2.7449 | 0.3006 | 0.1437 | 0.2521 | 0.2516 |
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+ | 2.7437 | 2.77 | 900 | 2.7425 | 0.3029 | 0.1479 | 0.2545 | 0.2543 |
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+ | 2.7437 | 2.86 | 930 | 2.7242 | 0.3028 | 0.1355 | 0.2318 | 0.2307 |
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+ | 2.7437 | 2.95 | 960 | 2.7232 | 0.3100 | 0.1474 | 0.2449 | 0.2443 |
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+ | 2.7437 | 3.05 | 990 | 2.7787 | 0.3036 | 0.1457 | 0.2465 | 0.2467 |
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+ | 2.1872 | 3.14 | 1020 | 2.7759 | 0.2957 | 0.1371 | 0.2394 | 0.2375 |
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+ | 2.1872 | 3.23 | 1050 | 2.7896 | 0.3105 | 0.1391 | 0.2403 | 0.2375 |
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+ | 2.1872 | 3.32 | 1080 | 2.7724 | 0.3121 | 0.1498 | 0.2452 | 0.2453 |
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+ | 2.1872 | 3.42 | 1110 | 2.7639 | 0.3204 | 0.1534 | 0.2556 | 0.2563 |
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+ | 2.1872 | 3.51 | 1140 | 2.7673 | 0.3103 | 0.1541 | 0.2529 | 0.2521 |
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+ | 2.1872 | 3.6 | 1170 | 2.7644 | 0.3059 | 0.1399 | 0.2450 | 0.2448 |
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+ | 2.1872 | 3.69 | 1200 | 2.7443 | 0.3186 | 0.1484 | 0.2554 | 0.2562 |
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+ | 2.1872 | 3.78 | 1230 | 2.7517 | 0.3045 | 0.1444 | 0.2522 | 0.2519 |
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+ | 2.1872 | 3.88 | 1260 | 2.7501 | 0.3039 | 0.1453 | 0.2534 | 0.2529 |
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+ | 2.1872 | 3.97 | 1290 | 2.7555 | 0.3039 | 0.1453 | 0.2534 | 0.2529 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 1.13.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.2