mt5-summarize-ar-en
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9127
- Rouge1: 0.4091
- Rouge2: 0.2216
- Rougel: 0.3747
- Rougelsum: 0.3744
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
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 90
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
4.731 | 0.16 | 100 | 3.7741 | 0.3274 | 0.1592 | 0.2979 | 0.2977 |
3.9076 | 0.32 | 200 | 3.3310 | 0.3424 | 0.1696 | 0.3120 | 0.3125 |
3.7287 | 0.48 | 300 | 3.0822 | 0.3820 | 0.1995 | 0.3503 | 0.3501 |
3.6632 | 0.64 | 400 | 3.0226 | 0.3977 | 0.2148 | 0.3621 | 0.3621 |
3.3942 | 0.8 | 500 | 2.9377 | 0.4041 | 0.2151 | 0.3675 | 0.3672 |
3.4731 | 0.96 | 600 | 2.9127 | 0.4091 | 0.2216 | 0.3747 | 0.3744 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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Base model
google/mt5-small