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---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: flan-t5-small-qclassifier_new_0.6-droprob_0.2-smooth_0.1-lr_1e-5-dcy_0.0001
  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-small-qclassifier_new_0.6-droprob_0.2-smooth_0.1-lr_1e-5-dcy_0.0001

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5710
- Precision: 0.7404
- Recall: 1.0
- F1: 0.8509

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.6235        | 1.0   | 193  | 0.5839          | 0.7395    | 1.0    | 0.8502 |
| 0.5853        | 2.0   | 386  | 0.5768          | 0.7395    | 1.0    | 0.8502 |
| 0.5783        | 3.0   | 579  | 0.5741          | 0.7395    | 1.0    | 0.8502 |
| 0.5739        | 4.0   | 772  | 0.5745          | 0.7395    | 1.0    | 0.8502 |
| 0.5714        | 5.0   | 965  | 0.5711          | 0.7395    | 1.0    | 0.8502 |
| 0.5695        | 6.0   | 1158 | 0.5710          | 0.7404    | 1.0    | 0.8509 |
| 0.5672        | 7.0   | 1351 | 0.5718          | 0.7404    | 1.0    | 0.8509 |
| 0.5639        | 8.0   | 1544 | 0.5715          | 0.7415    | 0.9956 | 0.8500 |
| 0.5624        | 9.0   | 1737 | 0.5725          | 0.7416    | 0.9912 | 0.8485 |
| 0.5619        | 10.0  | 1930 | 0.5715          | 0.7431    | 0.9860 | 0.8475 |
| 0.5613        | 11.0  | 2123 | 0.5720          | 0.7422    | 0.9842 | 0.8463 |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1