---
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