| | --- |
| | license: apache-2.0 |
| | base_model: philschmid/flan-t5-base-samsum |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: T5-model |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # T5-model |
| |
|
| | This model is a fine-tuned version of [philschmid/flan-t5-base-samsum](https://huggingface.co/philschmid/flan-t5-base-samsum) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7013 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 0.9849 | 0.8 | 10 | 0.8062 | |
| | | 0.9748 | 1.61 | 20 | 0.8026 | |
| | | 0.9772 | 2.41 | 30 | 0.7968 | |
| | | 0.979 | 3.22 | 40 | 0.7889 | |
| | | 0.9729 | 4.02 | 50 | 0.7793 | |
| | | 0.9479 | 4.82 | 60 | 0.7687 | |
| | | 0.9111 | 5.63 | 70 | 0.7577 | |
| | | 0.8956 | 6.43 | 80 | 0.7460 | |
| | | 0.8768 | 7.24 | 90 | 0.7338 | |
| | | 0.8566 | 8.04 | 100 | 0.7224 | |
| | | 0.8342 | 8.84 | 110 | 0.7120 | |
| | | 0.8273 | 9.65 | 120 | 0.7013 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.32.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| |
|
