Downloads · 30 days
5
11% of all-time downloads
aruca/pegasus_x-meeting-summarizer
pegasus_x-meeting-summarizer is a machine learning model from aruca. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
5
11% of all-time downloads
All-time downloads
44
Public
Parameters
272M
3.3 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors1.1 GB · 99%
From the Hugging Face model README
This model is a fine-tuned version of google/pegasus-x-base on the None dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.0461 | 0.05 | 10 | 2.6611 |
| 2.8656 | 0.11 | 20 | 2.3313 |
| 2.5122 | 0.16 | 30 | 2.1502 |
| 2.3941 | 0.21 | 40 | 2.0071 |
| 2.2445 | 0.27 | 50 | 1.9110 |
| 2.205 | 0.32 | 60 | 1.8388 |
| 2.1341 | 0.37 | 70 | 1.7728 |
| 1.9793 | 0.43 | 80 | 1.7464 |
| 1.8616 | 0.48 | 90 | 1.6930 |
| 1.8848 | 0.53 | 100 | 1.6589 |
| 1.8432 | 0.59 | 110 | 1.6232 |
| 1.7926 | 0.64 | 120 | 1.5996 |
| 1.7956 | 0.69 | 130 | 1.5898 |
| 1.7327 | 0.75 | 140 | 1.5683 |
| 1.8604 | 0.8 | 150 | 1.5416 |
| 1.7607 | 0.85 | 160 | 1.5211 |
| 1.7807 | 0.91 | 170 | 1.5025 |
| 1.6985 | 0.96 | 180 | 1.4906 |
| 1.6284 | 1.01 | 190 | 1.4781 |
| 1.5689 | 1.07 | 200 | 1.4680 |
| 1.4443 | 1.12 | 210 | 1.4602 |
| 1.564 | 1.17 | 220 | 1.4439 |
| 1.4824 | 1.23 | 230 | 1.4327 |
| 1.4463 | 1.28 | 240 | 1.4247 |
| 1.5279 | 1.33 | 250 | 1.4195 |
| 1.4522 | 1.39 | 260 | 1.3928 |
| 1.5307 | 1.44 | 270 | 1.3943 |
| 1.4977 | 1.49 | 280 | 1.3779 |
| 1.5163 | 1.55 | 290 | 1.3756 |
| 1.4912 | 1.6 | 300 | 1.3558 |
| 1.5212 | 1.65 | 310 | 1.3539 |
| 1.4575 | 1.71 | 320 | 1.3424 |
| 1.3196 | 1.76 | 330 | 1.3386 |
| 1.3492 | 1.81 | 340 | 1.3257 |
| 1.4383 | 1.87 | 350 | 1.3248 |
| 1.4726 | 1.92 | 360 | 1.3168 |
| 1.3496 | 1.97 | 370 | 1.3117 |
| 1.2985 | 2.03 | 380 | 1.3181 |
| 1.1527 | 2.08 | 390 | 1.3094 |
| 1.2825 | 2.13 | 400 | 1.3112 |
| 1.2893 | 2.19 | 410 | 1.2984 |
| 1.2076 | 2.24 | 420 | 1.2880 |
| 1.3257 | 2.29 | 430 | 1.2904 |
| 1.3425 | 2.35 | 440 | 1.2756 |
| 1.2814 | 2.4 | 450 | 1.2806 |
| 1.3054 | 2.45 | 460 | 1.2782 |
| 1.1984 | 2.51 | 470 | 1.2767 |
| 1.2381 | 2.56 | 480 | 1.2653 |
| 1.1786 | 2.61 | 490 | 1.2712 |
| 1.1959 | 2.67 | 500 | 1.2534 |
| 1.2749 | 2.72 | 510 | 1.2548 |
| 1.2894 | 2.77 | 520 | 1.2531 |
| 1.2131 | 2.83 | 530 | 1.2561 |
| 1.226 | 2.88 | 540 | 1.2459 |
| 1.1534 | 2.93 | 550 | 1.2466 |
| 1.2492 | 2.99 | 560 | 1.2446 |