bert2gpt2SUMM-finetuned-mlsum

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This model is used for french summarization

• Problem type: Summarization
• Model ID: 980832493
• CO2 Emissions (in grams): 0.10685501288084795

This model is a fine-tuned version of Chemsseddine/bert2gpt2SUMM on the None dataset. It achieves the following results on the evaluation set:

• Loss: 4.03749418258667
• Rouge1: 28.8384
• Rouge2: 10.7511
• RougeL: 27.0842
• RougeLsum: 27.5118
• Gen Len: 22.0625

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	33199	4.03749	28.8384	10.7511	27.0842	27.5118	22.0625