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---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-small-lamp-4u-finetuned-3
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-small-lamp-4u-finetuned-3
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co./google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4088
- Rouge1: 0.1634
- Rouge2: 0.0510
- Rougel: 0.1494
- Rougelsum: 0.1500
## 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: 8
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.6388 | 1.0 | 1566 | 2.5235 | 0.1413 | 0.0452 | 0.1311 | 0.1316 |
| 2.5039 | 2.0 | 3132 | 2.4539 | 0.1469 | 0.0474 | 0.1354 | 0.1359 |
| 2.401 | 3.0 | 4698 | 2.4320 | 0.1525 | 0.0486 | 0.1409 | 0.1414 |
| 2.3748 | 4.0 | 6264 | 2.4193 | 0.1528 | 0.0495 | 0.1414 | 0.1417 |
| 2.2997 | 5.0 | 7830 | 2.4120 | 0.1559 | 0.0490 | 0.1427 | 0.1430 |
| 2.2742 | 6.0 | 9396 | 2.4042 | 0.1562 | 0.0508 | 0.1436 | 0.1438 |
| 2.2404 | 7.0 | 10962 | 2.4039 | 0.1584 | 0.0515 | 0.1457 | 0.1461 |
| 2.2249 | 8.0 | 12528 | 2.4010 | 0.1624 | 0.0509 | 0.1491 | 0.1495 |
| 2.1985 | 9.0 | 14094 | 2.3993 | 0.1622 | 0.0520 | 0.1493 | 0.1501 |
| 2.1509 | 10.0 | 15660 | 2.3993 | 0.1599 | 0.0505 | 0.1454 | 0.1462 |
| 2.1226 | 11.0 | 17226 | 2.4026 | 0.1631 | 0.0519 | 0.1498 | 0.1503 |
| 2.107 | 12.0 | 18792 | 2.4040 | 0.1623 | 0.0513 | 0.1487 | 0.1491 |
| 2.0855 | 13.0 | 20358 | 2.4049 | 0.1634 | 0.0517 | 0.1493 | 0.1498 |
| 2.0678 | 14.0 | 21924 | 2.4028 | 0.1631 | 0.0515 | 0.1489 | 0.1495 |
| 2.0899 | 15.0 | 23490 | 2.4052 | 0.1628 | 0.0510 | 0.1489 | 0.1496 |
| 2.0777 | 16.0 | 25056 | 2.4050 | 0.1628 | 0.0503 | 0.1493 | 0.1498 |
| 2.0572 | 17.0 | 26622 | 2.4076 | 0.1620 | 0.0511 | 0.1481 | 0.1488 |
| 2.0408 | 18.0 | 28188 | 2.4066 | 0.1625 | 0.0510 | 0.1487 | 0.1495 |
| 2.0538 | 19.0 | 29754 | 2.4076 | 0.1635 | 0.0510 | 0.1496 | 0.1503 |
| 2.0283 | 20.0 | 31320 | 2.4088 | 0.1634 | 0.0510 | 0.1494 | 0.1500 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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