| | --- |
| | license: apache-2.0 |
| | base_model: google-t5/t5-large |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - bleu |
| | model-index: |
| | - name: fft-t5-large/adversarial_qa_dbert_based_on |
| | 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. --> |
| |
|
| | # fft-t5-large/adversarial_qa_dbert_based_on |
| |
|
| | This model is a fine-tuned version of [google-t5/t5-large](https://huggingface.co/google-t5/t5-large) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.1381 |
| | - Exact Match: 0.3467 |
| | - Bleu: 0.3083 |
| |
|
| | ## 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: 0.0002 |
| | - train_batch_size: 2 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - num_devices: 4 |
| | - total_train_batch_size: 8 |
| | - total_eval_batch_size: 64 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5.0 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Exact Match | Bleu | |
| | |:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:| |
| | | 1.0162 | 1.0 | 63 | 0.7607 | 0.2754 | 0.2749 | |
| | | 0.3929 | 2.0 | 126 | 0.7943 | 0.2959 | 0.2412 | |
| | | 0.1542 | 3.0 | 189 | 1.0053 | 0.3018 | 0.2720 | |
| | | 0.0544 | 4.0 | 252 | 1.1005 | 0.3457 | 0.3185 | |
| | | 0.0239 | 5.0 | 315 | 1.1381 | 0.3467 | 0.3083 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.41.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| |
|
