metadata
license: apache-2.0
base_model: lidiya/bart-large-xsum-samsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: cnn_xsum_samsum_model
results: []
cnn_xsum_samsum_model
This model is a fine-tuned version of lidiya/bart-large-xsum-samsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6585
- Rouge1: 0.4194
- Rouge2: 0.1959
- Rougel: 0.2948
- Rougelsum: 0.3902
- Gen Len: 60.8916
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: 16
- eval_batch_size: 16
- seed: 42
- 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.6501 | 1.0 | 836 | 1.6017 | 0.4143 | 0.194 | 0.2912 | 0.3845 | 60.7718 |
| 1.3162 | 2.0 | 1672 | 1.5954 | 0.4113 | 0.1908 | 0.2891 | 0.3819 | 61.3206 |
| 1.1452 | 3.0 | 2508 | 1.5853 | 0.4196 | 0.1964 | 0.2945 | 0.3899 | 60.928 |
| 1.012 | 4.0 | 3344 | 1.6293 | 0.4201 | 0.1967 | 0.2952 | 0.3911 | 60.7965 |
| 0.9368 | 5.0 | 4180 | 1.6585 | 0.4194 | 0.1959 | 0.2948 | 0.3902 | 60.8916 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2