---
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