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bart-large-cnn-samsum-acsi-ami
This model is a fine-tuned version of philschmid/bart-large-cnn-samsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.1361
- Rouge1: 39.7563
- Rouge2: 11.1286
- Rougel: 23.2632
- Rougelsum: 36.5664
- Gen Len: 108.15
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 20 | 3.2095 | 39.8174 | 11.5559 | 24.0296 | 36.3048 | 108.5 |
| No log | 2.0 | 40 | 3.1361 | 39.7563 | 11.1286 | 23.2632 | 36.5664 | 108.15 |
| No log | 3.0 | 60 | 3.1599 | 41.79 | 12.0967 | 23.5336 | 37.6859 | 122.95 |
| No log | 4.0 | 80 | 3.2878 | 42.3161 | 12.2801 | 23.9352 | 38.2391 | 122.7 |
| No log | 5.0 | 100 | 3.3671 | 40.7968 | 10.7336 | 22.9434 | 36.4383 | 129.225 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2
