---
library_name: transformers
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: 1.9154
- Accuracy: 0.7753
- Precision: 0.7868
- Recall: 0.7553
- F1 score: 0.7707

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | Precision | Recall | F1 score |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 1.0303        | 0.4205 | 2500  | 0.8270          | 0.7471   | 0.8088    | 0.6471 | 0.7190   |
| 0.9652        | 0.8410 | 5000  | 0.6861          | 0.7118   | 0.9245    | 0.4612 | 0.6154   |
| 0.9232        | 1.2616 | 7500  | 0.9442          | 0.7471   | 0.8017    | 0.6565 | 0.7219   |
| 0.8457        | 1.6821 | 10000 | 0.9311          | 0.7471   | 0.7869    | 0.6776 | 0.7282   |
| 0.7519        | 2.1026 | 12500 | 1.0887          | 0.7682   | 0.8065    | 0.7059 | 0.7528   |
| 0.6462        | 2.5231 | 15000 | 1.1780          | 0.7706   | 0.8125    | 0.7035 | 0.7541   |
| 0.642         | 2.9437 | 17500 | 1.2434          | 0.7718   | 0.7954    | 0.7318 | 0.7623   |
| 0.4436        | 3.3642 | 20000 | 1.3026          | 0.76     | 0.7931    | 0.7035 | 0.7456   |
| 0.3762        | 3.7847 | 22500 | 1.6051          | 0.7659   | 0.7678    | 0.7624 | 0.7651   |
| 0.2798        | 4.2052 | 25000 | 1.9011          | 0.7671   | 0.7683    | 0.7647 | 0.7665   |
| 0.2012        | 4.6257 | 27500 | 1.9154          | 0.7753   | 0.7868    | 0.7553 | 0.7707   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1