learning_rate: 1e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
lr_scheduler_type: constant
num_epochs: 8
label_smoothing_factor: 0.1

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
35.3040	1.0	1128	3.8356	0.4562	0.2151	0.3057	0.3056
32.9291	2.0	2256	3.6969	0.4756	0.2304	0.3237	0.3239
31.6170	3.0	3384	3.5895	0.4849	0.2372	0.3314	0.3314
30.4512	4.0	4512	3.4988	0.4863	0.2388	0.3343	0.3344
29.9236	5.0	5640	3.4431	0.4915	0.2443	0.3402	0.3403
29.3764	6.0	6768	3.3960	0.5022	0.2513	0.3459	0.3459
29.0224	7.0	7896	3.3521	0.5072	0.2553	0.3517	0.3517
28.6897	8.0	9024	3.3116	0.509	0.2569	0.354	0.3542

Fatoumataa/mt5-bambara-resumer-final

mt5-bambara-resumer-final