hosseinmhmdkhani/google-mt5-base-lora-finetuned-persian-news
013
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google-mt5-base-lora-finetuned-persian-news
This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9099
- Rouge1 Precision: 59.4386
- Rouge1 Recall: 60.3359
- Rouge1 F1: 58.6755
- Rouge2 Precision: 42.2757
- Rouge2 Recall: 43.1573
- Rouge2 F1: 41.7994
- Rougel Precision: 51.4347
- Rougel Recall: 52.3226
- Rougel F1: 50.8172
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: 0.0005
- trainbatchsize: 4
- evalbatchsize: 4
- seed: 42
- gradientaccumulationsteps: 8
- totaltrainbatch_size: 32
- optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
- lrschedulertype: cosine
- lrschedulerwarmup_steps: 0.1
- num_epochs: 4
Training results
Framework versions
- PEFT 0.20.0
- Transformers 5.14.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
