---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_keras_callback
model-index:
- name: bedus-creation/eng-limbu-t5-manual-002
  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. -->

# bedus-creation/eng-limbu-t5-manual-002

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: 3.0687
- Validation Loss: 3.7774
- 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 |
|:----------:|:---------------:|:-----:|
| 6.7285     | 5.8526          | 0     |
| 5.8608     | 5.3145          | 1     |
| 5.3625     | 5.0804          | 2     |
| 5.1012     | 4.9629          | 3     |
| 4.9323     | 4.8258          | 4     |
| 4.7733     | 4.7266          | 5     |
| 4.6924     | 4.6181          | 6     |
| 4.5603     | 4.5446          | 7     |
| 4.4889     | 4.4844          | 8     |
| 4.4311     | 4.4172          | 9     |
| 4.3759     | 4.3850          | 10    |
| 4.3222     | 4.3224          | 11    |
| 4.2802     | 4.2932          | 12    |
| 4.2507     | 4.2517          | 13    |
| 4.1858     | 4.2192          | 14    |
| 4.1643     | 4.2057          | 15    |
| 4.1406     | 4.2012          | 16    |
| 4.0881     | 4.1809          | 17    |
| 4.0782     | 4.1407          | 18    |
| 4.0536     | 4.1458          | 19    |
| 4.0260     | 4.1167          | 20    |
| 4.0093     | 4.1147          | 21    |
| 3.9739     | 4.0881          | 22    |
| 3.9548     | 4.0896          | 23    |
| 3.9533     | 4.0832          | 24    |
| 3.9363     | 4.0328          | 25    |
| 3.9258     | 4.0340          | 26    |
| 3.8973     | 4.0176          | 27    |
| 3.8789     | 4.0131          | 28    |
| 3.8784     | 4.0032          | 29    |
| 3.8391     | 3.9896          | 30    |
| 3.8506     | 3.9902          | 31    |
| 3.8081     | 3.9742          | 32    |
| 3.8068     | 3.9699          | 33    |
| 3.7911     | 3.9409          | 34    |
| 3.7909     | 3.9411          | 35    |
| 3.7658     | 3.9416          | 36    |
| 3.7317     | 3.9270          | 37    |
| 3.7404     | 3.9225          | 38    |
| 3.7321     | 3.9159          | 39    |
| 3.7112     | 3.9071          | 40    |
| 3.7039     | 3.9003          | 41    |
| 3.6980     | 3.8723          | 42    |
| 3.6639     | 3.8921          | 43    |
| 3.6612     | 3.8674          | 44    |
| 3.6497     | 3.8624          | 45    |
| 3.6284     | 3.8694          | 46    |
| 3.6403     | 3.8701          | 47    |
| 3.5968     | 3.8516          | 48    |
| 3.5749     | 3.8435          | 49    |
| 3.5751     | 3.8545          | 50    |
| 3.5736     | 3.8304          | 51    |
| 3.5722     | 3.8247          | 52    |
| 3.5431     | 3.8396          | 53    |
| 3.5280     | 3.8265          | 54    |
| 3.5288     | 3.8225          | 55    |
| 3.5014     | 3.8248          | 56    |
| 3.5046     | 3.7864          | 57    |
| 3.5144     | 3.8151          | 58    |
| 3.4876     | 3.8117          | 59    |
| 3.4744     | 3.8099          | 60    |
| 3.4667     | 3.8110          | 61    |
| 3.4503     | 3.8165          | 62    |
| 3.4516     | 3.7818          | 63    |
| 3.4484     | 3.8165          | 64    |
| 3.4146     | 3.8282          | 65    |
| 3.3911     | 3.8151          | 66    |
| 3.4345     | 3.7842          | 67    |
| 3.4155     | 3.7777          | 68    |
| 3.3755     | 3.8011          | 69    |
| 3.3595     | 3.7737          | 70    |
| 3.3727     | 3.7744          | 71    |
| 3.3670     | 3.7683          | 72    |
| 3.3493     | 3.7721          | 73    |
| 3.3337     | 3.7927          | 74    |
| 3.3260     | 3.7670          | 75    |
| 3.3160     | 3.7802          | 76    |
| 3.3120     | 3.7885          | 77    |
| 3.3101     | 3.7675          | 78    |
| 3.2842     | 3.7837          | 79    |
| 3.2765     | 3.7607          | 80    |
| 3.2684     | 3.7805          | 81    |
| 3.2576     | 3.7578          | 82    |
| 3.2637     | 3.7661          | 83    |
| 3.2414     | 3.7964          | 84    |
| 3.2241     | 3.7806          | 85    |
| 3.2294     | 3.7762          | 86    |
| 3.2067     | 3.7526          | 87    |
| 3.1882     | 3.7809          | 88    |
| 3.2020     | 3.7670          | 89    |
| 3.1646     | 3.7671          | 90    |
| 3.1873     | 3.7586          | 91    |
| 3.1619     | 3.7843          | 92    |
| 3.1608     | 3.7573          | 93    |
| 3.1648     | 3.7654          | 94    |
| 3.1107     | 3.7811          | 95    |
| 3.1221     | 3.7974          | 96    |
| 3.0947     | 3.7810          | 97    |
| 3.1046     | 3.7647          | 98    |
| 3.0687     | 3.7774          | 99    |


### Framework versions

- Transformers 4.33.2
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.13.3