---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
model-index:
- name: flan-t5-base-absa-multitask-joint
  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-absa-multitask-joint

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: 0.1276

## 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: 0.1
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.5367        | 0.16  | 200  | 0.5267          |
| 0.5433        | 0.32  | 400  | 0.3377          |
| 0.3887        | 0.47  | 600  | 0.2688          |
| 0.3123        | 0.63  | 800  | 0.2205          |
| 0.2724        | 0.79  | 1000 | 0.2282          |
| 0.2627        | 0.95  | 1200 | 0.1881          |
| 0.2294        | 1.11  | 1400 | 0.1827          |
| 0.2221        | 1.27  | 1600 | 0.1844          |
| 0.1957        | 1.42  | 1800 | 0.1860          |
| 0.2007        | 1.58  | 2000 | 0.1674          |
| 0.1866        | 1.74  | 2200 | 0.1628          |
| 0.175         | 1.9   | 2400 | 0.1636          |
| 0.1637        | 2.06  | 2600 | 0.1506          |
| 0.1541        | 2.22  | 2800 | 0.1505          |
| 0.1484        | 2.37  | 3000 | 0.1465          |
| 0.1442        | 2.53  | 3200 | 0.1496          |
| 0.1338        | 2.69  | 3400 | 0.1355          |
| 0.1415        | 2.85  | 3600 | 0.1369          |
| 0.1435        | 3.01  | 3800 | 0.1343          |
| 0.1242        | 3.16  | 4000 | 0.1348          |
| 0.1227        | 3.32  | 4200 | 0.1328          |
| 0.1229        | 3.48  | 4400 | 0.1287          |
| 0.1272        | 3.64  | 4600 | 0.1280          |
| 0.1132        | 3.8   | 4800 | 0.1264          |
| 0.1131        | 3.96  | 5000 | 0.1276          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2