---
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LED-Base-NSPCC
  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. -->

# LED-Base-NSPCC

This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8734
- Rouge1: 0.4910
- Rouge2: 0.2207
- Rougel: 0.2847
- Rougelsum: 0.2840

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.4662        | 0.9947 | 47   | 1.9451          | 0.4528 | 0.1809 | 0.2560 | 0.2558    |
| 1.6508        | 1.9894 | 94   | 1.8497          | 0.4889 | 0.2146 | 0.2720 | 0.2716    |
| 1.2549        | 2.9841 | 141  | 1.8268          | 0.4812 | 0.2092 | 0.2756 | 0.2753    |
| 0.9955        | 3.9788 | 188  | 1.8734          | 0.4910 | 0.2207 | 0.2847 | 0.2840    |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1