---
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_large_FINAL_Task2_semantic_pred
  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_large_FINAL_Task2_semantic_pred

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: 1.2525
- Accuracy: 0.8814
- Precision: 0.8988
- Recall: 0.8604
- F1 score: 0.8792

## 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: 10

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | Precision | Recall | F1 score |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 0.8828        | 0.4257 | 2500  | 0.8908          | 0.8257   | 0.7870    | 0.8946 | 0.8373   |
| 0.7602        | 0.8515 | 5000  | 0.9174          | 0.8371   | 0.8395    | 0.8348 | 0.8371   |
| 0.6466        | 1.2772 | 7500  | 0.6703          | 0.8671   | 0.9216    | 0.8034 | 0.8584   |
| 0.5325        | 1.7030 | 10000 | 0.6555          | 0.8657   | 0.8560    | 0.8803 | 0.8680   |
| 0.5041        | 2.1287 | 12500 | 0.8110          | 0.8557   | 0.8592    | 0.8519 | 0.8555   |
| 0.3444        | 2.5545 | 15000 | 0.8804          | 0.8729   | 0.8701    | 0.8775 | 0.8738   |
| 0.3324        | 2.9802 | 17500 | 0.8064          | 0.8686   | 0.8866    | 0.8462 | 0.8659   |
| 0.2141        | 3.4060 | 20000 | 0.7677          | 0.8686   | 0.8529    | 0.8917 | 0.8719   |
| 0.2403        | 3.8317 | 22500 | 0.6505          | 0.8686   | 0.9218    | 0.8063 | 0.8602   |
| 0.1754        | 4.2575 | 25000 | 1.1009          | 0.8543   | 0.832     | 0.8889 | 0.8595   |
| 0.1455        | 4.6832 | 27500 | 0.9066          | 0.8557   | 0.8189    | 0.9145 | 0.8641   |
| 0.1004        | 5.1090 | 30000 | 1.0664          | 0.8686   | 0.8607    | 0.8803 | 0.8704   |
| 0.0522        | 5.5347 | 32500 | 1.2579          | 0.8729   | 0.8808    | 0.8632 | 0.8719   |
| 0.0742        | 5.9605 | 35000 | 1.0095          | 0.8786   | 0.8912    | 0.8632 | 0.8770   |
| 0.0435        | 6.3862 | 37500 | 1.3122          | 0.8614   | 0.8342    | 0.9031 | 0.8673   |
| 0.0263        | 6.8120 | 40000 | 1.1928          | 0.8743   | 0.8725    | 0.8775 | 0.875    |
| 0.0226        | 7.2377 | 42500 | 1.2052          | 0.8757   | 0.8882    | 0.8604 | 0.8741   |
| 0.0219        | 7.6635 | 45000 | 1.1019          | 0.8829   | 0.8854    | 0.8803 | 0.8829   |
| 0.0271        | 8.0892 | 47500 | 1.2264          | 0.88     | 0.8761    | 0.8860 | 0.8810   |
| 0.0073        | 8.5150 | 50000 | 1.2916          | 0.8786   | 0.8866    | 0.8689 | 0.8777   |
| 0.0197        | 8.9407 | 52500 | 1.1860          | 0.88     | 0.8915    | 0.8661 | 0.8786   |
| 0.0066        | 9.3665 | 55000 | 1.2615          | 0.88     | 0.8938    | 0.8632 | 0.8783   |
| 0.0098        | 9.7922 | 57500 | 1.2525          | 0.8814   | 0.8988    | 0.8604 | 0.8792   |


### Framework versions

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