metadata
library_name: transformers
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Bart-CNN-dataset
results: []
Bart-CNN-dataset
This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2222
- Rouge1: 0.4398
- Rouge2: 0.1996
- Rougel: 0.2964
- Rougelsum: 0.4096
- Gen Len: 95.364
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 250 | 1.4136 | 0.4361 | 0.2058 | 0.2957 | 0.4075 | 99.678 |
| 1.3139 | 2.0 | 500 | 1.4521 | 0.444 | 0.2085 | 0.3035 | 0.4138 | 90.808 |
| 1.3139 | 3.0 | 750 | 1.5573 | 0.4409 | 0.2046 | 0.2945 | 0.4102 | 100.502 |
| 0.7471 | 4.0 | 1000 | 1.6873 | 0.4429 | 0.205 | 0.2985 | 0.4119 | 96.34 |
| 0.7471 | 5.0 | 1250 | 1.8544 | 0.4395 | 0.2016 | 0.2964 | 0.409 | 100.1 |
| 0.4392 | 6.0 | 1500 | 2.0239 | 0.4407 | 0.2012 | 0.2946 | 0.4085 | 97.476 |
| 0.4392 | 7.0 | 1750 | 2.1492 | 0.4409 | 0.199 | 0.2947 | 0.4101 | 94.41 |
| 0.2886 | 8.0 | 2000 | 2.2222 | 0.4398 | 0.1996 | 0.2964 | 0.4096 | 95.364 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3