---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_keras_callback
model-index:
- name: JuliusFx/dyu-fr-t5-small_v7
  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_v7

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: 1.9053
- Validation Loss: 3.0844
- 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 |
|:----------:|:---------------:|:-----:|
| 3.6620     | 3.3803          | 0     |
| 3.4472     | 3.2921          | 1     |
| 3.3525     | 3.2231          | 2     |
| 3.2837     | 3.1862          | 3     |
| 3.2322     | 3.1474          | 4     |
| 3.1837     | 3.1283          | 5     |
| 3.1428     | 3.0978          | 6     |
| 3.1095     | 3.0848          | 7     |
| 3.0765     | 3.0664          | 8     |
| 3.0453     | 3.0565          | 9     |
| 3.0144     | 3.0408          | 10    |
| 2.9884     | 3.0344          | 11    |
| 2.9633     | 3.0285          | 12    |
| 2.9377     | 3.0228          | 13    |
| 2.9175     | 3.0158          | 14    |
| 2.8979     | 3.0310          | 15    |
| 2.8737     | 3.0306          | 16    |
| 2.8575     | 3.0122          | 17    |
| 2.8343     | 3.0232          | 18    |
| 2.8178     | 3.0135          | 19    |
| 2.7992     | 3.0038          | 20    |
| 2.7791     | 3.0221          | 21    |
| 2.7636     | 3.0123          | 22    |
| 2.7430     | 3.0083          | 23    |
| 2.7286     | 3.0186          | 24    |
| 2.7083     | 2.9942          | 25    |
| 2.6964     | 2.9911          | 26    |
| 2.6792     | 2.9891          | 27    |
| 2.6580     | 3.0056          | 28    |
| 2.6414     | 3.0048          | 29    |
| 2.6329     | 3.0040          | 30    |
| 2.6213     | 3.0035          | 31    |
| 2.6042     | 3.0061          | 32    |
| 2.5913     | 3.0095          | 33    |
| 2.5720     | 3.0202          | 34    |
| 2.5590     | 3.0204          | 35    |
| 2.5429     | 3.0304          | 36    |
| 2.5352     | 3.0128          | 37    |
| 2.5162     | 2.9989          | 38    |
| 2.5086     | 3.0094          | 39    |
| 2.4949     | 3.0048          | 40    |
| 2.4799     | 3.0187          | 41    |
| 2.4703     | 3.0199          | 42    |
| 2.4537     | 3.0340          | 43    |
| 2.4468     | 3.0233          | 44    |
| 2.4317     | 3.0171          | 45    |
| 2.4195     | 3.0274          | 46    |
| 2.4079     | 3.0265          | 47    |
| 2.3948     | 3.0173          | 48    |
| 2.3852     | 3.0194          | 49    |
| 2.3728     | 3.0275          | 50    |
| 2.3631     | 3.0147          | 51    |
| 2.3525     | 3.0338          | 52    |
| 2.3401     | 3.0444          | 53    |
| 2.3303     | 3.0556          | 54    |
| 2.3145     | 3.0440          | 55    |
| 2.3057     | 3.0500          | 56    |
| 2.2951     | 3.0496          | 57    |
| 2.2830     | 3.0497          | 58    |
| 2.2690     | 3.0461          | 59    |
| 2.2646     | 3.0373          | 60    |
| 2.2503     | 3.0343          | 61    |
| 2.2457     | 3.0589          | 62    |
| 2.2343     | 3.0538          | 63    |
| 2.2285     | 3.0434          | 64    |
| 2.2146     | 3.0410          | 65    |
| 2.2048     | 3.0339          | 66    |
| 2.1913     | 3.0507          | 67    |
| 2.1803     | 3.0459          | 68    |
| 2.1747     | 3.0487          | 69    |
| 2.1641     | 3.0344          | 70    |
| 2.1547     | 3.0440          | 71    |
| 2.1461     | 3.0655          | 72    |
| 2.1403     | 3.0383          | 73    |
| 2.1267     | 3.0239          | 74    |
| 2.1161     | 3.0183          | 75    |
| 2.1010     | 3.0555          | 76    |
| 2.0980     | 3.0412          | 77    |
| 2.0894     | 3.0400          | 78    |
| 2.0806     | 3.0389          | 79    |
| 2.0744     | 3.0377          | 80    |
| 2.0591     | 3.0596          | 81    |
| 2.0525     | 3.0449          | 82    |
| 2.0465     | 3.0532          | 83    |
| 2.0385     | 3.0465          | 84    |
| 2.0232     | 3.0374          | 85    |
| 2.0231     | 3.0280          | 86    |
| 2.0089     | 3.0506          | 87    |
| 2.0031     | 3.0629          | 88    |
| 1.9959     | 3.0440          | 89    |
| 1.9854     | 3.0669          | 90    |
| 1.9776     | 3.0718          | 91    |
| 1.9698     | 3.0657          | 92    |
| 1.9591     | 3.0650          | 93    |
| 1.9529     | 3.0599          | 94    |
| 1.9483     | 3.0726          | 95    |
| 1.9429     | 3.0682          | 96    |
| 1.9271     | 3.0618          | 97    |
| 1.9208     | 3.0857          | 98    |
| 1.9053     | 3.0844          | 99    |


### Framework versions

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