mt5-small-amharic-text-summaization
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.9166
- eval_rouge1: 17.2202
- eval_rouge2: 9.6515
- eval_rougeL: 16.8757
- eval_rougeLsum: 16.8802
- eval_runtime: 189.6659
- eval_samples_per_second: 14.178
- eval_steps_per_second: 1.777
- epoch: 10.0
- step: 13450
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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Base model
google/mt5-small