---
library_name: transformers
base_model: Plasmoxy/flan-t5-small-gigatrue
tags:
- generated_from_trainer
model-index:
- name: flan-t5-small-gigatrue-INCS2S-0.5sparsity
  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. -->

# flan-t5-small-gigatrue-INCS2S-0.5sparsity

This model is a fine-tuned version of [Plasmoxy/flan-t5-small-gigatrue](https://huggingface.co/Plasmoxy/flan-t5-small-gigatrue) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0847

## 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: 0.0003
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 2.4167        | 0.1015 | 3000  | 2.1071          |
| 2.4079        | 0.2030 | 6000  | 2.0958          |
| 2.4015        | 0.3044 | 9000  | 2.0977          |
| 2.3987        | 0.4059 | 12000 | 2.0943          |
| 2.394         | 0.5074 | 15000 | 2.0944          |
| 2.394         | 0.6089 | 18000 | 2.0898          |
| 2.393         | 0.7104 | 21000 | 2.0893          |
| 2.3935        | 0.8119 | 24000 | 2.0877          |
| 2.3901        | 0.9133 | 27000 | 2.0885          |
| 2.3913        | 1.0148 | 30000 | 2.0869          |
| 2.3902        | 1.1163 | 33000 | 2.0872          |
| 2.3859        | 1.2178 | 36000 | 2.0861          |
| 2.3873        | 1.3193 | 39000 | 2.0853          |
| 2.3862        | 1.4207 | 42000 | 2.0844          |
| 2.3854        | 1.5222 | 45000 | 2.0845          |
| 2.3849        | 1.6237 | 48000 | 2.0866          |
| 2.3874        | 1.7252 | 51000 | 2.0856          |
| 2.3813        | 1.8267 | 54000 | 2.0839          |
| 2.3839        | 1.9282 | 57000 | 2.0839          |
| 2.3856        | 2.0296 | 60000 | 2.0846          |
| 2.3857        | 2.1311 | 63000 | 2.0853          |
| 2.3808        | 2.2326 | 66000 | 2.0851          |
| 2.3859        | 2.3341 | 69000 | 2.0847          |
| 2.3849        | 2.4356 | 72000 | 2.0849          |
| 2.3832        | 2.5370 | 75000 | 2.0846          |
| 2.3861        | 2.6385 | 78000 | 2.0846          |
| 2.3842        | 2.7400 | 81000 | 2.0849          |
| 2.3852        | 2.8415 | 84000 | 2.0848          |
| 2.3844        | 2.9430 | 87000 | 2.0847          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.20.3