---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-base-lamp-7t-finetuned-1
  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-base-lamp-7t-finetuned-1

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2121
- Rouge1: 0.5299
- Rouge2: 0.2730
- Rougel: 0.4776
- Rougelsum: 0.4930

## 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: 16
- 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_ratio: 0.05
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 7.0613        | 1.0   | 840   | 1.2605          | 0.5053 | 0.2462 | 0.4513 | 0.4657    |
| 1.3665        | 2.0   | 1680  | 1.2271          | 0.5124 | 0.2562 | 0.4600 | 0.4747    |
| 1.3009        | 3.0   | 2520  | 1.2114          | 0.5179 | 0.2613 | 0.4652 | 0.4802    |
| 1.2594        | 4.0   | 3360  | 1.2039          | 0.5229 | 0.2656 | 0.4677 | 0.4839    |
| 1.227         | 5.0   | 4200  | 1.1988          | 0.5247 | 0.2669 | 0.4698 | 0.4860    |
| 1.1918        | 6.0   | 5040  | 1.1966          | 0.5238 | 0.2698 | 0.4701 | 0.4860    |
| 1.1696        | 7.0   | 5880  | 1.1934          | 0.5261 | 0.2702 | 0.4723 | 0.4880    |
| 1.1285        | 8.0   | 6720  | 1.1933          | 0.5237 | 0.2693 | 0.4701 | 0.4849    |
| 1.1153        | 9.0   | 7560  | 1.1961          | 0.5263 | 0.2708 | 0.4724 | 0.4880    |
| 1.0927        | 10.0  | 8400  | 1.1961          | 0.5254 | 0.2691 | 0.4720 | 0.4874    |
| 1.0661        | 11.0  | 9240  | 1.2010          | 0.5234 | 0.2684 | 0.4698 | 0.4854    |
| 1.0634        | 12.0  | 10080 | 1.2003          | 0.5259 | 0.2723 | 0.4729 | 0.4885    |
| 1.046         | 13.0  | 10920 | 1.2019          | 0.5277 | 0.2726 | 0.4747 | 0.4907    |
| 1.0273        | 14.0  | 11760 | 1.2045          | 0.5309 | 0.2749 | 0.4776 | 0.4940    |
| 1.0218        | 15.0  | 12600 | 1.2077          | 0.5295 | 0.2728 | 0.4771 | 0.4925    |
| 1.0208        | 16.0  | 13440 | 1.2095          | 0.5303 | 0.2728 | 0.4775 | 0.4928    |
| 1.003         | 17.0  | 14280 | 1.2110          | 0.5301 | 0.2726 | 0.4772 | 0.4929    |
| 1.003         | 18.0  | 15120 | 1.2099          | 0.5314 | 0.2729 | 0.4781 | 0.4941    |
| 0.9893        | 19.0  | 15960 | 1.2115          | 0.5302 | 0.2737 | 0.4779 | 0.4933    |
| 0.9918        | 20.0  | 16800 | 1.2121          | 0.5299 | 0.2730 | 0.4776 | 0.4930    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0