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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_1
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_1
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: 0.7562
- Validation Loss: 0.8440
- Train Rouge1: 8.5573
- Train Rouge2: 1.2871
- Train Rougel: 8.4866
- Train Rougelsum: 8.5337
- Train Gen Len: 11.8812
- Epoch: 10
## 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 |
|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 5.3770 | 2.6665 | 4.5262 | 0.6931 | 4.5733 | 4.5733 | 8.9356 | 0 |
| 2.7256 | 2.0063 | 5.6931 | 1.3201 | 5.6518 | 5.6931 | 10.2277 | 1 |
| 2.0053 | 1.4899 | 7.7086 | 2.1782 | 7.7086 | 7.7086 | 11.3465 | 2 |
| 1.5782 | 1.2268 | 7.7086 | 2.1782 | 7.7086 | 7.7086 | 11.8168 | 3 |
| 1.3143 | 1.1257 | 8.6987 | 2.1782 | 8.6987 | 8.4866 | 11.9257 | 4 |
| 1.1311 | 1.0411 | 8.9816 | 2.2772 | 8.9109 | 8.9109 | 11.9406 | 5 |
| 1.0120 | 0.9954 | 8.9816 | 2.2772 | 8.9109 | 8.9109 | 11.9406 | 6 |
| 0.9320 | 0.9375 | 8.9816 | 2.2772 | 8.9109 | 8.9109 | 11.9208 | 7 |
| 0.8538 | 0.8867 | 8.9816 | 2.2772 | 8.9109 | 8.9109 | 11.8911 | 8 |
| 0.7999 | 0.8593 | 8.8166 | 1.7822 | 8.7459 | 8.7459 | 11.8861 | 9 |
| 0.7562 | 0.8440 | 8.5573 | 1.2871 | 8.4866 | 8.5337 | 11.8812 | 10 |
### Framework versions
- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1
|