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---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: expected_model_nov11
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. -->
# expected_model_nov11
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1943
- Rouge1: 72.751
- Rouge2: 64.531
- Rougel: 71.7809
- Rougelsum: 72.5858
- Gen Len: 16.4797
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 11.5118 | 0.68 | 200 | 0.4990 | 52.9797 | 43.7182 | 52.2591 | 52.9986 | 9.6068 |
| 0.4597 | 1.36 | 400 | 0.2770 | 71.5492 | 62.6473 | 70.6589 | 71.4471 | 16.4237 |
| 0.3259 | 2.03 | 600 | 0.2486 | 72.1475 | 63.0992 | 71.3032 | 72.0859 | 16.3983 |
| 0.273 | 2.71 | 800 | 0.2273 | 71.9258 | 63.3664 | 71.1095 | 71.7798 | 16.5339 |
| 0.2545 | 3.39 | 1000 | 0.2161 | 72.3257 | 63.5931 | 71.5259 | 72.3231 | 16.4322 |
| 0.2374 | 4.07 | 1200 | 0.2091 | 72.3551 | 63.9109 | 71.5349 | 72.2473 | 16.4746 |
| 0.2143 | 4.75 | 1400 | 0.2116 | 72.3027 | 63.8027 | 71.6227 | 72.221 | 16.439 |
| 0.2161 | 5.42 | 1600 | 0.1991 | 72.3081 | 63.7819 | 71.4337 | 72.2038 | 16.4712 |
| 0.1987 | 6.1 | 1800 | 0.2039 | 72.4605 | 64.0889 | 71.6023 | 72.3601 | 16.4864 |
| 0.1942 | 6.78 | 2000 | 0.2020 | 72.458 | 63.8879 | 71.4977 | 72.3096 | 16.4424 |
| 0.1826 | 7.46 | 2200 | 0.2000 | 72.2467 | 63.7052 | 71.3826 | 72.0909 | 16.4288 |
| 0.1867 | 8.14 | 2400 | 0.1965 | 72.417 | 64.0356 | 71.5254 | 72.3042 | 16.4983 |
| 0.1773 | 8.81 | 2600 | 0.1930 | 72.5715 | 64.1819 | 71.6728 | 72.501 | 16.4797 |
| 0.1875 | 9.49 | 2800 | 0.1943 | 72.751 | 64.531 | 71.7809 | 72.5858 | 16.4797 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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