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---
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-large-v1
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. -->
# flan-t5-large-v1
This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1673
- Rouge1: 74.1287
- Rouge2: 66.4339
- Rougel: 72.8596
- Rougelsum: 73.8679
- Gen Len: 16.3241
## 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: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 12.4521 | 0.85 | 200 | 0.2565 | 72.2564 | 62.6872 | 70.741 | 72.0604 | 15.9467 |
| 0.2538 | 1.7 | 400 | 0.1877 | 72.8835 | 64.0804 | 71.5277 | 72.642 | 16.3582 |
| 0.1804 | 2.55 | 600 | 0.1715 | 73.307 | 64.5027 | 72.2345 | 73.098 | 16.1429 |
| 0.1516 | 3.4 | 800 | 0.1675 | 73.9648 | 65.6244 | 72.8421 | 73.8516 | 16.2026 |
| 0.1331 | 4.26 | 1000 | 0.1609 | 73.7382 | 65.6094 | 72.5124 | 73.5658 | 16.3198 |
| 0.1205 | 5.11 | 1200 | 0.1656 | 74.2505 | 66.5083 | 73.1059 | 74.0956 | 16.3795 |
| 0.1113 | 5.96 | 1400 | 0.1593 | 74.2997 | 66.2497 | 73.2158 | 74.1265 | 16.3326 |
| 0.1031 | 6.81 | 1600 | 0.1643 | 74.2861 | 66.3972 | 73.1252 | 74.0796 | 16.2729 |
| 0.0909 | 7.66 | 1800 | 0.1638 | 73.7071 | 65.61 | 72.4082 | 73.5071 | 16.3262 |
| 0.0876 | 8.51 | 2000 | 0.1667 | 74.1477 | 66.0628 | 72.9115 | 73.9177 | 16.3198 |
| 0.0911 | 9.36 | 2200 | 0.1673 | 74.1287 | 66.4339 | 72.8596 | 73.8679 | 16.3241 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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