---
library_name: transformers
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: T5_128tokens_advice
  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. -->

# T5_128tokens_advice

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4632
- Accuracy: 0.7711
- F1: 0.7652
- Precision: 0.7624
- Recall: 0.7711

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.63          | 1.0   | 199  | 0.5496          | 0.7170   | 0.5988 | 0.5141    | 0.7170 |
| 0.6192        | 2.0   | 398  | 0.5315          | 0.7245   | 0.6768 | 0.6871    | 0.7245 |
| 0.4783        | 3.0   | 597  | 0.4725          | 0.7635   | 0.7403 | 0.7462    | 0.7635 |
| 0.497         | 4.0   | 796  | 0.4565          | 0.7623   | 0.7611 | 0.7601    | 0.7623 |
| 0.4039        | 5.0   | 995  | 0.4632          | 0.7711   | 0.7652 | 0.7624    | 0.7711 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0