metadata
base_model: google/pegasus-x-base
tags:
- generated_from_trainer
model-index:
- name: pegasus_x-meeting-summarizer-gpt3.5
results: []
pegasus_x-meeting-summarizer-gpt3.5
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:
- Loss: 1.6064
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: reduce_lr_on_plateau
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.7528 | 0.05 | 10 | 2.5788 |
| 2.7466 | 0.11 | 20 | 2.2694 |
| 2.4032 | 0.16 | 30 | 2.1298 |
| 2.3188 | 0.21 | 40 | 2.0389 |
| 2.1827 | 0.27 | 50 | 1.9788 |
| 2.1284 | 0.32 | 60 | 1.9291 |
| 2.1275 | 0.37 | 70 | 1.9024 |
| 2.0536 | 0.43 | 80 | 1.8587 |
| 1.9901 | 0.48 | 90 | 1.8407 |
| 1.9769 | 0.53 | 100 | 1.8211 |
| 1.9643 | 0.59 | 110 | 1.8048 |
| 1.8846 | 0.64 | 120 | 1.7921 |
| 1.9294 | 0.69 | 130 | 1.7837 |
| 1.903 | 0.75 | 140 | 1.7664 |
| 1.9329 | 0.8 | 150 | 1.7606 |
| 1.865 | 0.85 | 160 | 1.7493 |
| 1.8414 | 0.91 | 170 | 1.7404 |
| 1.8793 | 0.96 | 180 | 1.7310 |
| 1.8519 | 1.01 | 190 | 1.7165 |
| 1.7918 | 1.07 | 200 | 1.7132 |
| 1.7815 | 1.12 | 210 | 1.7087 |
| 1.7503 | 1.17 | 220 | 1.7019 |
| 1.7545 | 1.23 | 230 | 1.6937 |
| 1.7088 | 1.28 | 240 | 1.6905 |
| 1.7231 | 1.33 | 250 | 1.6862 |
| 1.7584 | 1.39 | 260 | 1.6807 |
| 1.7537 | 1.44 | 270 | 1.6762 |
| 1.7867 | 1.49 | 280 | 1.6685 |
| 1.7666 | 1.55 | 290 | 1.6642 |
| 1.7076 | 1.6 | 300 | 1.6580 |
| 1.6894 | 1.65 | 310 | 1.6596 |
| 1.7207 | 1.71 | 320 | 1.6535 |
| 1.6743 | 1.76 | 330 | 1.6565 |
| 1.7197 | 1.81 | 340 | 1.6491 |
| 1.7027 | 1.87 | 350 | 1.6438 |
| 1.7161 | 1.92 | 360 | 1.6388 |
| 1.7256 | 1.97 | 370 | 1.6368 |
| 1.6623 | 2.03 | 380 | 1.6370 |
| 1.6041 | 2.08 | 390 | 1.6402 |
| 1.6308 | 2.13 | 400 | 1.6289 |
| 1.6384 | 2.19 | 410 | 1.6333 |
| 1.6223 | 2.24 | 420 | 1.6291 |
| 1.6163 | 2.29 | 430 | 1.6212 |
| 1.6232 | 2.35 | 440 | 1.6267 |
| 1.6081 | 2.4 | 450 | 1.6302 |
| 1.619 | 2.45 | 460 | 1.6196 |
| 1.5802 | 2.51 | 470 | 1.6215 |
| 1.6313 | 2.56 | 480 | 1.6216 |
| 1.5968 | 2.61 | 490 | 1.6153 |
| 1.589 | 2.67 | 500 | 1.6137 |
| 1.6087 | 2.72 | 510 | 1.6129 |
| 1.5614 | 2.77 | 520 | 1.6085 |
| 1.6109 | 2.83 | 530 | 1.6067 |
| 1.596 | 2.88 | 540 | 1.6097 |
| 1.6343 | 2.93 | 550 | 1.5979 |
| 1.5774 | 2.99 | 560 | 1.6064 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2