metadata
license: mit
base_model: philschmid/bart-large-cnn-samsum
tags:
- generated_from_trainer
model-index:
- name: bart-model
results: []
bart-model
This model is a fine-tuned version of philschmid/bart-large-cnn-samsum on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6169
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.487 | 0.8 | 10 | 1.2019 |
| 1.3092 | 1.61 | 20 | 0.9905 |
| 1.0316 | 2.41 | 30 | 0.7841 |
| 0.8111 | 3.22 | 40 | 0.6587 |
| 0.7191 | 4.02 | 50 | 0.5964 |
| 0.5906 | 4.82 | 60 | 0.5613 |
| 0.5351 | 5.63 | 70 | 0.5393 |
| 0.4696 | 6.43 | 80 | 0.5429 |
| 0.4249 | 7.24 | 90 | 0.5287 |
| 0.3619 | 8.04 | 100 | 0.5577 |
| 0.3303 | 8.84 | 110 | 0.5794 |
| 0.2718 | 9.65 | 120 | 0.6169 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3