---
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