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---
license: apache-2.0
base_model: google/mt5-large
tags:
- generated_from_keras_callback
model-index:
- name: pakawadeep/mt5-large-finetuned-ctfl
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-large-finetuned-ctfl
This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 3.4642
- Validation Loss: 2.1307
- Train Rouge1: 5.9406
- Train Rouge2: 0.9406
- Train Rougel: 5.7756
- Train Rougelsum: 5.8463
- Train Gen Len: 11.2228
- Epoch: 6
## 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 |
|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 11.3596 | 5.2319 | 2.5366 | 0.5088 | 2.5148 | 2.4929 | 19.0 | 0 |
| 6.1803 | 3.1508 | 2.7057 | 0.5265 | 2.6846 | 2.6643 | 19.0 | 1 |
| 4.6767 | 2.5774 | 2.7471 | 0.5265 | 2.7054 | 2.6899 | 18.3218 | 2 |
| 3.8698 | 2.8216 | 2.9763 | 0.2200 | 2.8792 | 2.8987 | 16.6238 | 3 |
| 4.7045 | 2.7911 | 3.2793 | 0.5501 | 3.1484 | 3.2486 | 14.1881 | 4 |
| 4.0342 | 2.4191 | 5.9406 | 0.6365 | 5.7206 | 5.8306 | 10.6980 | 5 |
| 3.4642 | 2.1307 | 5.9406 | 0.9406 | 5.7756 | 5.8463 | 11.2228 | 6 |
### Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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