mbart-large-50-FR-summary
This model is a fine-tuned version of facebook/mbart-large-50 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.0592
- Rouge1: 0.2998
- Rouge2: 0.1263
- Rougel: 0.2412
- Rougelsum: 0.2416
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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
3.7346 | 1.0 | 1088 | 2.0456 | 0.2939 | 0.1209 | 0.2353 | 0.2360 |
1.7032 | 2.0 | 2176 | 1.9431 | 0.2924 | 0.1252 | 0.2359 | 0.2372 |
1.1491 | 3.0 | 3264 | 2.0827 | 0.2974 | 0.1266 | 0.2399 | 0.2413 |
0.7099 | 4.0 | 4352 | 2.3316 | 0.3013 | 0.1284 | 0.2426 | 0.2440 |
0.4321 | 5.0 | 5440 | 2.7126 | 0.2934 | 0.1225 | 0.2343 | 0.2356 |
0.262 | 6.0 | 6528 | 2.9308 | 0.3023 | 0.1294 | 0.2420 | 0.2430 |
0.1901 | 7.0 | 7616 | 3.0321 | 0.3026 | 0.1275 | 0.2412 | 0.2422 |
0.1932 | 8.0 | 8704 | 3.0592 | 0.2998 | 0.1263 | 0.2412 | 0.2416 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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