---
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_MT
  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_MT

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: 1.9144
- Accuracy: 0.7959
- Precision: 0.8188
- Recall: 0.76
- F1 score: 0.7883

## 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  | Accuracy | F1 score | Precision | Recall | Validation Loss |
|:-------------:|:------:|:-----:|:--------:|:--------:|:---------:|:------:|:---------------:|
| 1.1594        | 0.2103 | 2500  | 0.7306   | 0.6914   | 0.8091    | 0.6035 | 1.1807          |
| 0.956         | 0.4205 | 5000  | 0.78     | 0.7556   | 0.85      | 0.68   | 1.0125          |
| 0.8973        | 0.6308 | 7500  | 1.2023   | 0.7529   | 0.8772    | 0.5882 | 0.7042          |
| 0.9154        | 0.8410 | 10000 | 1.0591   | 0.7771   | 0.8458    | 0.6776 | 0.7524          |
| 0.8148        | 1.0513 | 12500 | 1.1675   | 0.7753   | 0.8087    | 0.7212 | 0.7624          |
| 0.6499        | 1.2616 | 15000 | 0.9862   | 0.8076   | 0.8501    | 0.7471 | 0.7952          |
| 0.6059        | 1.4718 | 17500 | 1.0780   | 0.7659   | 0.7404    | 0.8188 | 0.7777          |
| 0.5391        | 1.6821 | 20000 | 1.2307   | 0.7694   | 0.7928    | 0.7294 | 0.7598          |
| 0.479         | 1.8923 | 22500 | 1.2428   | 0.7735   | 0.7675    | 0.7847 | 0.7760          |
| 0.3085        | 2.1026 | 25000 | 1.3597   | 0.7676   | 0.7571    | 0.7882 | 0.7723          |
| 0.226         | 2.3129 | 27500 | 1.6552   | 0.7776   | 0.7757    | 0.7812 | 0.7784          |
| 0.2293        | 2.5231 | 30000 | 1.4472   | 0.7847   | 0.7909    | 0.7741 | 0.7824          |
| 0.2201        | 2.7334 | 32500 | 1.3059   | 0.7982   | 0.7972    | 0.8    | 0.7986          |
| 0.2119        | 2.9437 | 35000 | 1.6964   | 0.7882   | 0.7981    | 0.7718 | 0.7847          |
| 0.087         | 3.1539 | 37500 | 1.9933   | 0.7818   | 0.7801    | 0.7847 | 0.7824          |
| 0.102         | 3.3642 | 40000 | 1.6337   | 0.7859   | 0.7866    | 0.7847 | 0.7856          |
| 0.0925        | 3.5744 | 42500 | 1.8106   | 0.7894   | 0.7808    | 0.8047 | 0.7926          |
| 0.1071        | 3.7847 | 45000 | 1.6925   | 0.7865   | 0.7691    | 0.8188 | 0.7932          |
| 0.077         | 3.9950 | 47500 | 1.8706   | 0.7929   | 0.8044    | 0.7741 | 0.7890          |
| 0.036         | 4.2052 | 50000 | 2.0159   | 0.7865   | 0.7822    | 0.7941 | 0.7881          |
| 0.0534        | 4.4155 | 52500 | 1.9290   | 0.7882   | 0.7862    | 0.7918 | 0.7890          |
| 0.0516        | 4.6257 | 55000 | 1.9351   | 0.7959   | 0.8180    | 0.7612 | 0.7885          |
| 0.0471        | 4.8360 | 57500 | 1.9144   | 0.7959   | 0.8188    | 0.76   | 0.7883          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1