---
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: flanT5_Task2
  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. -->

# flanT5_Task2

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1812
- Accuracy: 0.7706
- Precision: 0.7861
- Recall: 0.7435
- F1 score: 0.7642

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | Precision | Recall | F1 score |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 1.1443        | 0.4205 | 2500  | 1.6635          | 0.6718   | 0.7829    | 0.4753 | 0.5915   |
| 1.0447        | 0.8410 | 5000  | 0.5585          | 0.7282   | 0.8149    | 0.5906 | 0.6849   |
| 0.9057        | 1.2616 | 7500  | 0.9051          | 0.7318   | 0.7275    | 0.7412 | 0.7343   |
| 0.8348        | 1.6821 | 10000 | 0.6307          | 0.7659   | 0.8742    | 0.6212 | 0.7263   |
| 0.7331        | 2.1026 | 12500 | 0.9500          | 0.7612   | 0.7489    | 0.7859 | 0.7669   |
| 0.6167        | 2.5231 | 15000 | 1.1524          | 0.7788   | 0.7970    | 0.7482 | 0.7718   |
| 0.6209        | 2.9437 | 17500 | 1.1690          | 0.7635   | 0.7872    | 0.7224 | 0.7534   |
| 0.4411        | 3.3642 | 20000 | 1.7563          | 0.7847   | 0.8438    | 0.6988 | 0.7645   |
| 0.4196        | 3.7847 | 22500 | 1.7767          | 0.7412   | 0.7204    | 0.7882 | 0.7528   |
| 0.292         | 4.2052 | 25000 | 2.0410          | 0.7624   | 0.7648    | 0.7576 | 0.7612   |
| 0.1791        | 4.6257 | 27500 | 2.1812          | 0.7706   | 0.7861    | 0.7435 | 0.7642   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0