---
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_Fact_U_T1
  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_Fact_U_T1

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: 2.1337
- Accuracy: 0.7718
- Precision: 0.8116
- Recall: 0.7308
- F1 score: 0.7690

## 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  | Accuracy | F1 score | Precision | Recall | Validation Loss |
|:-------------:|:------:|:-----:|:--------:|:--------:|:---------:|:------:|:---------------:|
| 1.221         | 0.3923 | 2500  | 0.6682   | 0.6659   | 0.6990    | 0.6357 | 1.1740          |
| 1.2301        | 0.7846 | 5000  | 0.6635   | 0.6977   | 0.6548    | 0.7466 | 1.5113          |
| 1.0764        | 1.1768 | 7500  | 0.6894   | 0.6741   | 0.7418    | 0.6176 | 1.2812          |
| 1.0245        | 1.5691 | 10000 | 0.7153   | 0.6676   | 0.8497    | 0.5498 | 1.2591          |
| 0.986         | 1.9614 | 12500 | 0.7259   | 0.6830   | 0.8567    | 0.5679 | 1.2615          |
| 0.8337        | 2.3537 | 15000 | 0.7271   | 0.6915   | 0.8387    | 0.5882 | 1.1350          |
| 0.807         | 2.7460 | 17500 | 0.74     | 0.7034   | 0.8647    | 0.5928 | 1.0071          |
| 0.7575        | 3.1382 | 20000 | 0.7353   | 0.6930   | 0.8729    | 0.5747 | 1.5670          |
| 0.5663        | 3.5305 | 22500 | 0.7435   | 0.7341   | 0.7963    | 0.6810 | 1.0824          |
| 0.6546        | 3.9228 | 25000 | 0.7424   | 0.7319   | 0.7973    | 0.6765 | 1.1824          |
| 0.4215        | 4.3151 | 27500 | 0.7435   | 0.7465   | 0.7679    | 0.7262 | 1.7775          |
| 0.4255        | 4.7074 | 30000 | 0.7635   | 0.7698   | 0.7796    | 0.7602 | 1.3931          |
| 0.3478        | 5.0996 | 32500 | 0.7635   | 0.7581   | 0.8098    | 0.7127 | 1.6014          |
| 0.2632        | 5.4919 | 35000 | 0.7447   | 0.7331   | 0.8032    | 0.6742 | 1.4911          |
| 0.2555        | 5.8842 | 37500 | 0.7588   | 0.7453   | 0.8264    | 0.6787 | 1.7558          |
| 0.2237        | 6.2765 | 40000 | 0.7588   | 0.7574   | 0.7940    | 0.7240 | 1.8132          |
| 0.1014        | 6.6688 | 42500 | 0.7647   | 0.7596   | 0.8103    | 0.7149 | 1.8028          |
| 0.15          | 7.0610 | 45000 | 0.7682   | 0.7733   | 0.7869    | 0.7602 | 1.7902          |
| 0.076         | 7.4533 | 47500 | 0.7706   | 0.7559   | 0.8459    | 0.6833 | 2.1883          |
| 0.1015        | 7.8456 | 50000 | 0.7694   | 0.7531   | 0.8494    | 0.6765 | 1.8640          |
| 0.0876        | 8.2379 | 52500 | 0.78     | 0.7823   | 0.8058    | 0.7602 | 2.0889          |
| 0.095         | 8.6302 | 55000 | 0.7859   | 0.7797   | 0.8385    | 0.7285 | 1.7835          |
| 0.0873        | 9.0224 | 57500 | 0.7718   | 0.7651   | 0.8229    | 0.7149 | 1.8784          |
| 0.0444        | 9.4147 | 60000 | 0.7706   | 0.7761   | 0.7879    | 0.7647 | 2.2505          |
| 0.0486        | 9.8070 | 62500 | 2.1337   | 0.7718   | 0.8116    | 0.7308 | 0.7690          |


### Framework versions

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