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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google/flan-t5-base
model-index:
- name: flan-t5-base-AR-LORA-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-base-AR-LORA-V1
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7887
- Exact Match: 28.3
- Gen Len: 3.592
## 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
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-----------:|:-------:|
| 1.1717 | 1.0 | 625 | 0.9465 | 18.9 | 3.82 |
| 0.8167 | 2.0 | 1250 | 0.8975 | 17.9 | 3.923 |
| 0.9046 | 3.0 | 1875 | 0.8691 | 25.4 | 3.338 |
| 0.9501 | 4.0 | 2500 | 0.8624 | 17.8 | 3.978 |
| 0.884 | 5.0 | 3125 | 0.8469 | 19.9 | 3.917 |
| 0.8418 | 6.0 | 3750 | 0.8356 | 24.8 | 3.596 |
| 0.877 | 7.0 | 4375 | 0.8261 | 19.0 | 3.926 |
| 0.804 | 8.0 | 5000 | 0.8147 | 23.0 | 3.732 |
| 0.8267 | 9.0 | 5625 | 0.8123 | 26.0 | 3.629 |
| 0.8979 | 10.0 | 6250 | 0.8132 | 24.5 | 3.685 |
| 0.8165 | 11.0 | 6875 | 0.8084 | 28.4 | 3.517 |
| 0.891 | 12.0 | 7500 | 0.8034 | 28.1 | 3.548 |
| 0.768 | 13.0 | 8125 | 0.8095 | 29.1 | 3.45 |
| 0.6895 | 14.0 | 8750 | 0.8018 | 27.7 | 3.553 |
| 0.7796 | 15.0 | 9375 | 0.7996 | 30.1 | 3.49 |
| 0.787 | 16.0 | 10000 | 0.8013 | 26.0 | 3.665 |
| 0.811 | 17.0 | 10625 | 0.7979 | 28.5 | 3.563 |
| 0.7858 | 18.0 | 11250 | 0.7991 | 26.4 | 3.64 |
| 0.8608 | 19.0 | 11875 | 0.7955 | 24.8 | 3.733 |
| 0.9044 | 20.0 | 12500 | 0.7913 | 25.9 | 3.662 |
| 0.9171 | 21.0 | 13125 | 0.7905 | 25.9 | 3.708 |
| 0.8093 | 22.0 | 13750 | 0.7918 | 28.1 | 3.596 |
| 0.7653 | 23.0 | 14375 | 0.7940 | 28.3 | 3.586 |
| 0.9361 | 24.0 | 15000 | 0.7887 | 28.3 | 3.592 |
| 0.6999 | 25.0 | 15625 | 0.7921 | 29.6 | 3.552 |
| 0.728 | 26.0 | 16250 | 0.7918 | 27.8 | 3.621 |
| 0.7169 | 27.0 | 16875 | 0.7908 | 27.2 | 3.628 |
| 0.6388 | 28.0 | 17500 | 0.7920 | 28.9 | 3.572 |
| 0.7302 | 29.0 | 18125 | 0.7920 | 28.8 | 3.573 |
| 0.7651 | 30.0 | 18750 | 0.7917 | 28.0 | 3.599 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.19.1
- Tokenizers 0.19.1 |