---
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
model-index:
- name: flan-t5-small-gigatrue-layercut-D34567
  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-layercut-D34567

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5359

## 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: 256
- eval_batch_size: 256
- 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 4.3671        | 0.2030 | 3000  | 3.6524          |
| 4.1172        | 0.4059 | 6000  | 3.5797          |
| 4.0808        | 0.6089 | 9000  | 3.5566          |
| 4.0681        | 0.8119 | 12000 | 3.5477          |
| 4.0631        | 1.0148 | 15000 | 3.5429          |
| 4.0603        | 1.2178 | 18000 | 3.5391          |
| 4.057         | 1.4207 | 21000 | 3.5384          |
| 4.0546        | 1.6237 | 24000 | 3.5375          |
| 4.0542        | 1.8267 | 27000 | 3.5366          |
| 4.0539        | 2.0296 | 30000 | 3.5363          |
| 4.0537        | 2.2326 | 33000 | 3.5361          |
| 4.0553        | 2.4356 | 36000 | 3.5360          |
| 4.0539        | 2.6385 | 39000 | 3.5361          |
| 4.0542        | 2.8415 | 42000 | 3.5359          |


### Framework versions

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