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---
license: apache-2.0
base_model: google/long-t5-tglobal-xl
tags:
- generated_from_trainer
datasets:
- learn3r/summ_screen_memsum_oracle
model-index:
- name: longt5_xl_sfd_memsum_30
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. -->
# longt5_xl_sfd_memsum_30
This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the learn3r/summ_screen_memsum_oracle dataset.
It achieves the following results on the evaluation set:
- Loss: 5.1322
## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 30.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.6697 | 0.97 | 14 | 2.4168 |
| 2.2272 | 1.95 | 28 | 2.2644 |
| 1.9024 | 2.99 | 43 | 2.2556 |
| 1.6554 | 3.97 | 57 | 2.4007 |
| 1.3619 | 4.94 | 71 | 2.4233 |
| 1.1577 | 5.98 | 86 | 2.6797 |
| 0.9584 | 6.96 | 100 | 2.8449 |
| 0.7197 | 8.0 | 115 | 3.0255 |
| 0.5756 | 8.97 | 129 | 3.1467 |
| 0.485 | 9.95 | 143 | 3.2976 |
| 0.4027 | 10.99 | 158 | 3.8111 |
| 0.2938 | 11.97 | 172 | 3.7330 |
| 0.2665 | 12.94 | 186 | 4.1417 |
| 0.2019 | 13.98 | 201 | 4.0316 |
| 0.1706 | 14.96 | 215 | 4.1357 |
| 0.1418 | 16.0 | 230 | 4.1022 |
| 0.1286 | 16.97 | 244 | 4.1198 |
| 0.1022 | 17.95 | 258 | 4.1862 |
| 0.1122 | 18.99 | 273 | 4.6386 |
| 0.093 | 19.97 | 287 | 4.6829 |
| 0.0783 | 20.94 | 301 | 4.6637 |
| 0.0698 | 21.98 | 316 | 4.7190 |
| 0.0688 | 22.96 | 330 | 5.0200 |
| 0.0633 | 24.0 | 345 | 4.7576 |
| 0.0609 | 24.97 | 359 | 4.7805 |
| 0.0553 | 25.95 | 373 | 4.7338 |
| 0.0503 | 26.99 | 388 | 5.1409 |
| 0.0471 | 27.97 | 402 | 5.1463 |
| 0.0472 | 28.94 | 416 | 5.1636 |
| 0.0376 | 29.22 | 420 | 5.1322 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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