metadata
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: test_sum_abs_bart-base_interpret_stops
results: []
test_sum_abs_bart-base_interpret_stops
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.2138
- Rouge1: 0.1463
- Rouge2: 0.033
- Rougel: 0.1107
- Rougelsum: 0.1107
- Gen Len: 20.0
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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.5259 | 1.0 | 3109 | 3.2984 | 0.1437 | 0.0332 | 0.1086 | 0.1086 | 20.0 |
| 3.4331 | 2.0 | 6218 | 3.2446 | 0.1464 | 0.0329 | 0.1107 | 0.1108 | 20.0 |
| 3.3512 | 3.0 | 9327 | 3.2226 | 0.146 | 0.0325 | 0.1105 | 0.1105 | 20.0 |
| 3.319 | 4.0 | 12436 | 3.2138 | 0.1463 | 0.033 | 0.1107 | 0.1107 | 20.0 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2