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---
license: apache-2.0
base_model: google/long-t5-tglobal-base
tags:
- generated_from_trainer
datasets:
- eur-lex-sum
model-index:
- name: LongT5_no_extraction_V1
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_no_extraction_V1
This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the eur-lex-sum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3639
## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 3.2571 | 0.9963 | 68 | 1.8571 |
| 2.6516 | 1.9927 | 136 | 1.7238 |
| 2.2687 | 2.9890 | 204 | 1.6153 |
| 2.0466 | 4.0 | 273 | 1.5414 |
| 1.9659 | 4.9963 | 341 | 1.4955 |
| 1.8813 | 5.9927 | 409 | 1.4752 |
| 1.8277 | 6.9890 | 477 | 1.4571 |
| 1.7626 | 8.0 | 546 | 1.4437 |
| 1.7528 | 8.9963 | 614 | 1.4315 |
| 1.7249 | 9.9927 | 682 | 1.4229 |
| 1.6981 | 10.9890 | 750 | 1.4126 |
| 1.6559 | 12.0 | 819 | 1.4061 |
| 1.6599 | 12.9963 | 887 | 1.3983 |
| 1.6465 | 13.9927 | 955 | 1.3994 |
| 1.6282 | 14.9890 | 1023 | 1.3923 |
| 1.5906 | 16.0 | 1092 | 1.3873 |
| 1.6035 | 16.9963 | 1160 | 1.3878 |
| 1.5909 | 17.9927 | 1228 | 1.3851 |
| 1.5802 | 18.9890 | 1296 | 1.3799 |
| 1.5481 | 20.0 | 1365 | 1.3860 |
| 1.5607 | 20.9963 | 1433 | 1.3745 |
| 1.5517 | 21.9927 | 1501 | 1.3736 |
| 1.5436 | 22.9890 | 1569 | 1.3735 |
| 1.5126 | 24.0 | 1638 | 1.3728 |
| 1.5289 | 24.9963 | 1706 | 1.3739 |
| 1.5234 | 25.9927 | 1774 | 1.3706 |
| 1.5179 | 26.9890 | 1842 | 1.3671 |
| 1.4908 | 28.0 | 1911 | 1.3680 |
| 1.5057 | 28.9963 | 1979 | 1.3688 |
| 1.5026 | 29.9927 | 2047 | 1.3649 |
| 1.498 | 30.9890 | 2115 | 1.3662 |
| 1.4866 | 32.0 | 2184 | 1.3655 |
| 1.493 | 32.9963 | 2252 | 1.3644 |
| 1.4877 | 33.9927 | 2320 | 1.3669 |
| 1.4858 | 34.9890 | 2388 | 1.3650 |
| 1.465 | 36.0 | 2457 | 1.3649 |
| 1.4822 | 36.9963 | 2525 | 1.3647 |
| 1.4797 | 37.9927 | 2593 | 1.3644 |
| 1.4803 | 38.9890 | 2661 | 1.3640 |
| 1.4548 | 39.8535 | 2720 | 1.3639 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.19.1
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