---
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