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library_name: transformers
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-rouge-durga-q1-clean
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mt5-rouge-durga-q1-clean
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7819
- Rouge1: 0.3074
- Rouge2: 0.0953
- Rougel: 0.3026
- Rougelsum: 0.3008
## 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:
- learning_rate: 0.0003
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 15.8442 | 1.0 | 3 | 11.1246 | 0.0148 | 0.0015 | 0.0152 | 0.0151 |
| 13.0661 | 2.0 | 6 | 9.3553 | 0.0226 | 0.0052 | 0.0219 | 0.0217 |
| 11.7048 | 3.0 | 9 | 8.0317 | 0.0198 | 0.0029 | 0.0177 | 0.0190 |
| 8.87 | 4.0 | 12 | 7.1382 | 0.0461 | 0.0105 | 0.0423 | 0.0406 |
| 11.0893 | 5.0 | 15 | 6.7905 | 0.0611 | 0.0106 | 0.0512 | 0.0503 |
| 9.8787 | 6.0 | 18 | 6.5255 | 0.0900 | 0.0224 | 0.0800 | 0.0782 |
| 9.8189 | 7.0 | 21 | 6.7007 | 0.0944 | 0.0231 | 0.0876 | 0.0861 |
| 8.2022 | 8.0 | 24 | 6.2109 | 0.0953 | 0.0227 | 0.0899 | 0.0910 |
| 8.5899 | 9.0 | 27 | 5.9520 | 0.0965 | 0.0171 | 0.0897 | 0.0914 |
| 7.5305 | 10.0 | 30 | 5.5748 | 0.0855 | 0.0157 | 0.0841 | 0.0821 |
| 7.0381 | 11.0 | 33 | 5.2219 | 0.0622 | 0.0095 | 0.0592 | 0.0585 |
| 6.675 | 12.0 | 36 | 4.8006 | 0.0529 | 0.0048 | 0.0499 | 0.0489 |
| 7.4134 | 13.0 | 39 | 4.3795 | 0.0693 | 0.0079 | 0.0635 | 0.0610 |
| 5.8722 | 14.0 | 42 | 3.9322 | 0.1060 | 0.0128 | 0.1003 | 0.1009 |
| 4.5875 | 15.0 | 45 | 3.5017 | 0.1012 | 0.0069 | 0.0968 | 0.0968 |
| 5.3675 | 16.0 | 48 | 3.1927 | 0.0944 | 0.0020 | 0.0915 | 0.0913 |
| 4.2999 | 17.0 | 51 | 2.8956 | 0.0890 | 0.0091 | 0.0831 | 0.0849 |
| 4.3349 | 18.0 | 54 | 2.7138 | 0.1164 | 0.0074 | 0.1114 | 0.1128 |
| 3.9688 | 19.0 | 57 | 2.5350 | 0.1122 | 0.0 | 0.1122 | 0.1121 |
| 4.2931 | 20.0 | 60 | 2.4138 | 0.1122 | 0.0 | 0.1122 | 0.1121 |
| 3.8427 | 21.0 | 63 | 2.3127 | 0.1122 | 0.0 | 0.1122 | 0.1121 |
| 3.2991 | 22.0 | 66 | 2.2054 | 0.1122 | 0.0 | 0.1122 | 0.1121 |
| 3.1351 | 23.0 | 69 | 2.1069 | 0.1122 | 0.0 | 0.1122 | 0.1121 |
| 3.023 | 24.0 | 72 | 2.0208 | 0.1142 | 0.0 | 0.1140 | 0.1139 |
| 3.4366 | 25.0 | 75 | 1.9500 | 0.1793 | 0.0352 | 0.1713 | 0.1711 |
| 2.7941 | 26.0 | 78 | 1.9068 | 0.3104 | 0.0909 | 0.3016 | 0.3005 |
| 2.9454 | 27.0 | 81 | 1.8419 | 0.3086 | 0.0940 | 0.3009 | 0.2984 |
| 2.6117 | 28.0 | 84 | 1.8775 | 0.3135 | 0.0955 | 0.3086 | 0.3067 |
| 2.6785 | 29.0 | 87 | 1.7772 | 0.3020 | 0.0946 | 0.2987 | 0.2968 |
| 2.7523 | 30.0 | 90 | 1.7819 | 0.3074 | 0.0953 | 0.3026 | 0.3008 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1
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