20231205_Bart-lg-samsum_TBD_Summ_Tr01
This model is a fine-tuned version of linydub/bart-large-samsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0913
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: 1e-05
- train_batch_size: 3
- eval_batch_size: 8
- seed: 42
- 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 |
|---|---|---|---|
| No log | 1.0 | 401 | 2.8537 |
| 5.39 | 2.0 | 802 | 0.8892 |
| 0.8114 | 3.0 | 1203 | 0.8283 |
| 0.5189 | 4.0 | 1604 | 0.8503 |
| 0.3804 | 5.0 | 2005 | 0.9076 |
| 0.3804 | 6.0 | 2406 | 0.9787 |
| 0.2618 | 7.0 | 2807 | 1.0719 |
| 0.2015 | 8.0 | 3208 | 1.0913 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.14.1
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Base model
linydub/bart-large-samsum