---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: continue_pretrain_t5_base_more_tokens
  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. -->

# continue_pretrain_t5_base_more_tokens

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9713
- Rouge: {'rouge1': 0.1482362658062074, 'rouge2': 0.13930032282405375, 'rougeL': 0.14788192707063608, 'rougeLsum': 0.14808345907939782}
- Exact Match: {'exact_match': 0.0}

## 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: 2e-05
- train_batch_size: 14
- eval_batch_size: 14
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 28
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge                                                                                                                           | Exact Match                            |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------:|
| 0.1018        | 1.0   | 1786 | 4.8212          | {'rouge1': 0.08214263320457528, 'rouge2': 0.07664435994602323, 'rougeL': 0.08165082402731275, 'rougeLsum': 0.08195136874817986} | {'exact_match': 0.0007692307692307692} |
| 0.0492        | 2.0   | 3572 | 4.9667          | {'rouge1': 0.14646008210615485, 'rouge2': 0.13764314957947393, 'rougeL': 0.14609763499439285, 'rougeLsum': 0.1462918679871027}  | {'exact_match': 0.0}                   |
| 0.0495        | 3.0   | 5358 | 4.9713          | {'rouge1': 0.1482362658062074, 'rouge2': 0.13930032282405375, 'rougeL': 0.14788192707063608, 'rougeLsum': 0.14808345907939782}  | {'exact_match': 0.0}                   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1