---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_keras_callback
model-index:
- name: JuliusFx/dyu-fr-t5-small_v8
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# JuliusFx/dyu-fr-t5-small_v8

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.8793
- Validation Loss: 2.9071
- Epoch: 99

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 3.1481     | 3.2663          | 0     |
| 3.0205     | 3.2024          | 1     |
| 2.9712     | 3.1559          | 2     |
| 2.9209     | 3.1465          | 3     |
| 2.8848     | 3.1125          | 4     |
| 2.8512     | 3.1014          | 5     |
| 2.8239     | 3.0771          | 6     |
| 2.7965     | 3.0641          | 7     |
| 2.7743     | 3.0431          | 8     |
| 2.7505     | 3.0327          | 9     |
| 2.7325     | 3.0072          | 10    |
| 2.7153     | 3.0060          | 11    |
| 2.6904     | 2.9950          | 12    |
| 2.6750     | 2.9895          | 13    |
| 2.6554     | 2.9700          | 14    |
| 2.6400     | 2.9632          | 15    |
| 2.6220     | 2.9534          | 16    |
| 2.6059     | 2.9505          | 17    |
| 2.5913     | 2.9536          | 18    |
| 2.5779     | 2.9485          | 19    |
| 2.5624     | 2.9349          | 20    |
| 2.5469     | 2.9307          | 21    |
| 2.5341     | 2.9224          | 22    |
| 2.5223     | 2.9114          | 23    |
| 2.5093     | 2.8996          | 24    |
| 2.4995     | 2.9065          | 25    |
| 2.4855     | 2.8974          | 26    |
| 2.4706     | 2.8926          | 27    |
| 2.4589     | 2.9075          | 28    |
| 2.4521     | 2.8921          | 29    |
| 2.4380     | 2.9055          | 30    |
| 2.4243     | 2.8930          | 31    |
| 2.4131     | 2.8871          | 32    |
| 2.4065     | 2.8894          | 33    |
| 2.3911     | 2.8890          | 34    |
| 2.3833     | 2.8757          | 35    |
| 2.3724     | 2.8778          | 36    |
| 2.3628     | 2.8874          | 37    |
| 2.3556     | 2.8687          | 38    |
| 2.3441     | 2.8653          | 39    |
| 2.3321     | 2.8794          | 40    |
| 2.3203     | 2.8827          | 41    |
| 2.3118     | 2.8778          | 42    |
| 2.3027     | 2.8955          | 43    |
| 2.2903     | 2.8778          | 44    |
| 2.2821     | 2.8751          | 45    |
| 2.2760     | 2.8655          | 46    |
| 2.2592     | 2.8763          | 47    |
| 2.2534     | 2.8643          | 48    |
| 2.2466     | 2.8716          | 49    |
| 2.2363     | 2.8728          | 50    |
| 2.2279     | 2.8688          | 51    |
| 2.2225     | 2.8822          | 52    |
| 2.2133     | 2.8690          | 53    |
| 2.2025     | 2.8551          | 54    |
| 2.1937     | 2.8605          | 55    |
| 2.1863     | 2.8441          | 56    |
| 2.1776     | 2.8576          | 57    |
| 2.1732     | 2.8435          | 58    |
| 2.1640     | 2.8448          | 59    |
| 2.1530     | 2.8422          | 60    |
| 2.1438     | 2.8640          | 61    |
| 2.1360     | 2.8648          | 62    |
| 2.1302     | 2.8689          | 63    |
| 2.1213     | 2.8787          | 64    |
| 2.1170     | 2.8816          | 65    |
| 2.1016     | 2.8655          | 66    |
| 2.0986     | 2.8713          | 67    |
| 2.0892     | 2.8776          | 68    |
| 2.0876     | 2.8912          | 69    |
| 2.0722     | 2.8901          | 70    |
| 2.0678     | 2.8549          | 71    |
| 2.0607     | 2.8883          | 72    |
| 2.0544     | 2.8681          | 73    |
| 2.0481     | 2.8637          | 74    |
| 2.0358     | 2.8739          | 75    |
| 2.0347     | 2.8705          | 76    |
| 2.0232     | 2.8724          | 77    |
| 2.0225     | 2.8619          | 78    |
| 2.0096     | 2.8687          | 79    |
| 2.0038     | 2.8561          | 80    |
| 1.9969     | 2.8560          | 81    |
| 1.9873     | 2.8755          | 82    |
| 1.9880     | 2.8745          | 83    |
| 1.9758     | 2.8648          | 84    |
| 1.9711     | 2.8808          | 85    |
| 1.9635     | 2.8721          | 86    |
| 1.9512     | 2.8739          | 87    |
| 1.9526     | 2.8836          | 88    |
| 1.9442     | 2.8862          | 89    |
| 1.9364     | 2.8969          | 90    |
| 1.9311     | 2.8948          | 91    |
| 1.9234     | 2.9150          | 92    |
| 1.9154     | 2.9048          | 93    |
| 1.9057     | 2.9040          | 94    |
| 1.9057     | 2.9043          | 95    |
| 1.8981     | 2.8895          | 96    |
| 1.8923     | 2.9031          | 97    |
| 1.8797     | 2.9221          | 98    |
| 1.8793     | 2.9071          | 99    |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2