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---
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
model-index:
- name: DATASET_PACSUM
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. -->
# DATASET_PACSUM
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5461
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.8648 | 0.1 | 10 | 2.8816 |
| 2.9889 | 0.2 | 20 | 2.7866 |
| 3.0516 | 0.3 | 30 | 2.7394 |
| 2.6605 | 0.4 | 40 | 2.7132 |
| 2.8093 | 0.5 | 50 | 2.6759 |
| 2.9206 | 0.6 | 60 | 2.6607 |
| 2.8094 | 0.7 | 70 | 2.6576 |
| 2.5233 | 0.8 | 80 | 2.6327 |
| 2.6508 | 0.9 | 90 | 2.6117 |
| 2.8456 | 1.0 | 100 | 2.5861 |
| 2.4622 | 1.1 | 110 | 2.5942 |
| 2.2871 | 1.2 | 120 | 2.5751 |
| 2.4482 | 1.3 | 130 | 2.5776 |
| 2.4079 | 1.4 | 140 | 2.5777 |
| 2.2842 | 1.5 | 150 | 2.5621 |
| 2.6267 | 1.6 | 160 | 2.5463 |
| 2.3895 | 1.7 | 170 | 2.5503 |
| 2.2786 | 1.8 | 180 | 2.5470 |
| 2.3628 | 1.9 | 190 | 2.5420 |
| 2.2809 | 2.0 | 200 | 2.5367 |
| 2.2726 | 2.1 | 210 | 2.5405 |
| 2.1934 | 2.2 | 220 | 2.5676 |
| 2.2447 | 2.3 | 230 | 2.5399 |
| 2.4508 | 2.4 | 240 | 2.5435 |
| 2.2969 | 2.5 | 250 | 2.5490 |
| 2.4206 | 2.6 | 260 | 2.5317 |
| 2.0131 | 2.7 | 270 | 2.5378 |
| 2.0025 | 2.8 | 280 | 2.5492 |
| 2.2179 | 2.9 | 290 | 2.5280 |
| 2.2082 | 3.0 | 300 | 2.5190 |
| 1.9491 | 3.1 | 310 | 2.5608 |
| 2.291 | 3.2 | 320 | 2.5448 |
| 2.0431 | 3.3 | 330 | 2.5319 |
| 2.0671 | 3.4 | 340 | 2.5529 |
| 2.1939 | 3.5 | 350 | 2.5388 |
| 2.0606 | 3.6 | 360 | 2.5306 |
| 2.0088 | 3.7 | 370 | 2.5557 |
| 2.1919 | 3.8 | 380 | 2.5317 |
| 2.2516 | 3.9 | 390 | 2.5290 |
| 1.9401 | 4.0 | 400 | 2.5404 |
| 2.1101 | 4.1 | 410 | 2.5354 |
| 1.8906 | 4.2 | 420 | 2.5520 |
| 1.9808 | 4.3 | 430 | 2.5488 |
| 1.8195 | 4.4 | 440 | 2.5496 |
| 1.8512 | 4.5 | 450 | 2.5535 |
| 2.0464 | 4.6 | 460 | 2.5519 |
| 2.0176 | 4.7 | 470 | 2.5450 |
| 2.0686 | 4.8 | 480 | 2.5460 |
| 2.0267 | 4.9 | 490 | 2.5463 |
| 1.8617 | 5.0 | 500 | 2.5461 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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