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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_40
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_40
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: 5.2679
## 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: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 40.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.5238 | 0.97 | 28 | 2.3147 |
| 2.1298 | 1.98 | 57 | 2.2837 |
| 1.7525 | 2.99 | 86 | 2.3335 |
| 1.2954 | 4.0 | 115 | 2.4995 |
| 1.0518 | 4.97 | 143 | 2.8326 |
| 0.7083 | 5.98 | 172 | 2.9095 |
| 0.5124 | 6.99 | 201 | 3.4108 |
| 0.4503 | 8.0 | 230 | 3.4459 |
| 0.3145 | 8.97 | 258 | 3.5216 |
| 0.2573 | 9.98 | 287 | 4.0127 |
| 0.213 | 10.99 | 316 | 3.9714 |
| 0.1682 | 12.0 | 345 | 3.8427 |
| 0.1396 | 12.97 | 373 | 4.2025 |
| 0.1363 | 13.98 | 402 | 4.4012 |
| 0.1148 | 14.99 | 431 | 4.7174 |
| 0.0907 | 16.0 | 460 | 4.4980 |
| 0.0942 | 16.97 | 488 | 4.7024 |
| 0.0765 | 17.98 | 517 | 4.3482 |
| 0.0799 | 18.99 | 546 | 4.5386 |
| 0.073 | 20.0 | 575 | 4.5889 |
| 0.0825 | 20.97 | 603 | 4.6817 |
| 0.0616 | 21.98 | 632 | 5.0263 |
| 0.0677 | 22.99 | 661 | 4.5804 |
| 0.0571 | 24.0 | 690 | 4.8399 |
| 0.0525 | 24.97 | 718 | 4.9350 |
| 0.081 | 25.98 | 747 | 4.6903 |
| 0.0505 | 26.99 | 776 | 5.0005 |
| 0.0576 | 28.0 | 805 | 5.0196 |
| 0.0448 | 28.97 | 833 | 5.1100 |
| 0.0457 | 29.98 | 862 | 5.0008 |
| 0.0442 | 30.99 | 891 | 5.5093 |
| 0.0391 | 32.0 | 920 | 5.4296 |
| 0.0392 | 32.97 | 948 | 5.2357 |
| 0.0376 | 33.98 | 977 | 5.2266 |
| 0.0381 | 34.99 | 1006 | 5.2630 |
| 0.0339 | 36.0 | 1035 | 5.3532 |
| 0.0377 | 36.97 | 1063 | 5.4443 |
| 0.0336 | 37.98 | 1092 | 5.0809 |
| 0.0316 | 38.96 | 1120 | 5.2679 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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