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---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_keras_callback
model-index:
- name: pakawadeep/mt5-base-finetuned-ctfl-augmented
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. -->
# pakawadeep/mt5-base-finetuned-ctfl-augmented
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.4325
- Validation Loss: 0.7749
- Train Rouge1: 8.6103
- Train Rouge2: 0.7921
- Train Rougel: 8.6987
- Train Rougelsum: 8.6987
- Train Gen Len: 11.8713
- Epoch: 29
## 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 | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch |
|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 6.9468 | 2.5770 | 1.3751 | 0.2405 | 1.3339 | 1.3916 | 8.5050 | 0 |
| 3.5520 | 2.0970 | 5.5693 | 0.8251 | 5.5487 | 5.6106 | 10.8564 | 1 |
| 2.7376 | 2.2001 | 5.1568 | 1.3201 | 4.9505 | 5.1155 | 10.0099 | 2 |
| 2.4757 | 1.8936 | 6.2706 | 1.1881 | 6.2235 | 6.3885 | 10.3614 | 3 |
| 2.1064 | 1.5432 | 7.4045 | 1.6832 | 7.2136 | 7.4116 | 11.1040 | 4 |
| 1.8167 | 1.3532 | 8.4866 | 2.1782 | 8.4158 | 8.6987 | 11.5644 | 5 |
| 1.6032 | 1.1789 | 8.6987 | 2.1782 | 8.4866 | 8.6987 | 11.8267 | 6 |
| 1.4351 | 1.1083 | 8.6987 | 2.1782 | 8.4866 | 8.6987 | 11.9059 | 7 |
| 1.3021 | 1.0607 | 8.9109 | 2.3762 | 8.8048 | 8.9816 | 11.9604 | 8 |
| 1.2060 | 1.0120 | 8.9109 | 2.3762 | 8.8048 | 8.9816 | 11.9455 | 9 |
| 1.1182 | 0.9736 | 8.6987 | 1.8812 | 8.6987 | 8.7694 | 11.9703 | 10 |
| 1.0551 | 0.9458 | 8.6987 | 1.8812 | 8.6987 | 8.7694 | 11.9406 | 11 |
| 0.9862 | 0.9170 | 8.5926 | 1.3861 | 8.5337 | 8.6516 | 11.9455 | 12 |
| 0.9324 | 0.8727 | 8.5101 | 1.3861 | 8.4807 | 8.5691 | 11.9208 | 13 |
| 0.8809 | 0.8625 | 8.7459 | 1.8812 | 8.6987 | 8.8166 | 11.9257 | 14 |
| 0.8334 | 0.8322 | 8.4512 | 1.3861 | 8.4158 | 8.4866 | 11.9307 | 15 |
| 0.7864 | 0.8009 | 7.9562 | 0.7921 | 7.7793 | 7.9915 | 11.9010 | 16 |
| 0.7542 | 0.8049 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8465 | 17 |
| 0.7157 | 0.7914 | 8.4512 | 1.3861 | 8.4158 | 8.4866 | 11.9356 | 18 |
| 0.6806 | 0.7787 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8812 | 19 |
| 0.6492 | 0.7813 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8861 | 20 |
| 0.6222 | 0.7654 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8713 | 21 |
| 0.5934 | 0.7588 | 8.4512 | 1.3861 | 8.4158 | 8.4866 | 11.8960 | 22 |
| 0.5648 | 0.7596 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8861 | 23 |
| 0.5423 | 0.7755 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8762 | 24 |
| 0.5180 | 0.7640 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8861 | 25 |
| 0.4931 | 0.7582 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8416 | 26 |
| 0.4738 | 0.7671 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8614 | 27 |
| 0.4544 | 0.7644 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8465 | 28 |
| 0.4325 | 0.7749 | 8.6103 | 0.7921 | 8.6987 | 8.6987 | 11.8713 | 29 |
### Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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