metadata
library_name: transformers
license: apache-2.0
base_model: sshleifer/distilbart-cnn-12-6
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: cleaned_ds
results: []
datasets:
- ccdv/arxiv-summarization
language:
- en
TextSummizer
This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6837
- Rouge1: 0.421
- Rouge2: 0.1462
- Rougel: 0.248
- Rougelsum: 0.3488
- Generated Length: 120.0345
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Generated Length |
|---|---|---|---|---|---|---|---|---|
| 3.0367 | 1.0 | 609 | 2.7608 | 0.4091 | 0.1389 | 0.2423 | 0.3401 | 122.0861 |
| 2.6396 | 2.0 | 1218 | 2.6925 | 0.4206 | 0.1468 | 0.2485 | 0.3508 | 124.4791 |
| 2.4229 | 3.0 | 1827 | 2.6837 | 0.421 | 0.1462 | 0.248 | 0.3488 | 120.0345 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1