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

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0625

## 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7161        | 0.32  | 200  | 0.2886          |
| 0.2835        | 0.63  | 400  | 0.1959          |
| 0.2043        | 0.95  | 600  | 0.1378          |
| 0.1379        | 1.26  | 800  | 0.1329          |
| 0.1174        | 1.58  | 1000 | 0.1180          |
| 0.1118        | 1.9   | 1200 | 0.0967          |
| 0.0739        | 2.21  | 1400 | 0.0947          |
| 0.0646        | 2.53  | 1600 | 0.1028          |
| 0.0639        | 2.84  | 1800 | 0.0797          |
| 0.0496        | 3.16  | 2000 | 0.0803          |
| 0.0405        | 3.48  | 2200 | 0.0795          |
| 0.04          | 3.79  | 2400 | 0.0653          |
| 0.0327        | 4.11  | 2600 | 0.0691          |
| 0.0293        | 4.42  | 2800 | 0.0631          |
| 0.0203        | 4.74  | 3000 | 0.0668          |
| 0.0257        | 5.06  | 3200 | 0.0575          |
| 0.0186        | 5.37  | 3400 | 0.0648          |
| 0.016         | 5.69  | 3600 | 0.0625          |


### Framework versions

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