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---
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results_pegasus2-_wiki
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results_pegasus2-_wiki
This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0771
- Rouge1: 0.2644
- Rouge2: 0.1159
- Rougel: 0.264
- Rougelsum: 0.2635
- Gen Len: 248.7564
## 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: 4e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 2.6037 | 0.5222 | 500 | 0.2910 | 0.0 | 0.0 | 0.0 | 0.0 | 223.1886 |
| 0.2787 | 1.0444 | 1000 | 0.2403 | 0.0515 | 0.0 | 0.0525 | 0.052 | 221.6974 |
| 0.2284 | 1.5666 | 1500 | 0.1922 | 0.0607 | 0.0 | 0.0621 | 0.0614 | 246.9666 |
| 0.1827 | 2.0888 | 2000 | 0.1775 | 0.1271 | 0.0176 | 0.129 | 0.1278 | 247.4322 |
| 0.167 | 2.6110 | 2500 | 0.1437 | 0.1591 | 0.0347 | 0.1597 | 0.1598 | 248.3084 |
| 0.1537 | 3.1332 | 3000 | 0.1301 | 0.1765 | 0.047 | 0.1765 | 0.1754 | 249.0864 |
| 0.14 | 3.6554 | 3500 | 0.1183 | 0.2082 | 0.059 | 0.2086 | 0.2077 | 248.2633 |
| 0.1306 | 4.1775 | 4000 | 0.1092 | 0.2095 | 0.0599 | 0.209 | 0.2083 | 246.5972 |
| 0.1272 | 4.6997 | 4500 | 0.1024 | 0.2181 | 0.0719 | 0.2177 | 0.2172 | 247.3752 |
| 0.1177 | 5.2219 | 5000 | 0.1013 | 0.2217 | 0.0725 | 0.2217 | 0.2211 | 247.4224 |
| 0.1123 | 5.7441 | 5500 | 0.0929 | 0.2242 | 0.0797 | 0.2249 | 0.2243 | 247.277 |
| 0.1114 | 6.2663 | 6000 | 0.0887 | 0.2335 | 0.0839 | 0.2334 | 0.233 | 247.3399 |
| 0.1073 | 6.7885 | 6500 | 0.0835 | 0.2452 | 0.0976 | 0.2461 | 0.2452 | 249.2043 |
| 0.1025 | 7.3107 | 7000 | 0.0821 | 0.2458 | 0.0971 | 0.2456 | 0.2455 | 246.2063 |
| 0.1009 | 7.8329 | 7500 | 0.0821 | 0.251 | 0.1009 | 0.2509 | 0.2508 | 248.7642 |
| 0.1004 | 8.3551 | 8000 | 0.0834 | 0.2583 | 0.1058 | 0.2587 | 0.258 | 248.7525 |
| 0.0965 | 8.8773 | 8500 | 0.0791 | 0.2621 | 0.116 | 0.2622 | 0.2621 | 248.7407 |
| 0.0975 | 9.3995 | 9000 | 0.0781 | 0.2619 | 0.1147 | 0.2613 | 0.2608 | 248.4185 |
| 0.0941 | 9.9217 | 9500 | 0.0771 | 0.2644 | 0.1159 | 0.264 | 0.2635 | 248.7564 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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