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contemmcm/
a0b648d6e0c2065718b942c275329ea8

Name: a0b648d6e0c2065718b942c275329ea8
Rating: 2.5 (5 reviews)

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a0b648d6e0c2065718b942c275329ea8

This model is a fine-tuned version of google/mt5-large on the Helsinki-NLP/opus_books [fr-nl] dataset. It achieves the following results on the evaluation set:

Loss: 1.4275
Data Size: 1.0
Epoch Runtime: 401.2085
Bleu: 10.9394

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 32
total_eval_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Data Size	Epoch Runtime	Bleu
No log	0	0	25.5985	0	30.6092	0.0176
No log	1	1000	18.8340	0.0078	34.4953	0.0230
No log	2	2000	8.0071	0.0156	38.2032	0.0307
No log	3	3000	6.0234	0.0312	45.3777	0.0448
0.3703	4	4000	2.8579	0.0625	57.8481	0.5543
3.1761	5	5000	2.2244	0.125	81.9571	7.3657
0.16	6	6000	1.9558	0.25	128.6183	6.1663
0.2037	7	7000	1.7958	0.5	221.6526	7.0443
2.017	8.0	8000	1.6592	1.0	402.3181	8.0500
1.8557	9.0	9000	1.5824	1.0	401.6877	8.8124
1.7318	10.0	10000	1.5295	1.0	400.8879	9.2664
1.6393	11.0	11000	1.4937	1.0	401.0046	9.5815
1.5502	12.0	12000	1.4601	1.0	401.2907	9.8645
1.4799	13.0	13000	1.4510	1.0	403.5631	10.0124
1.4131	14.0	14000	1.4298	1.0	406.0393	10.2133
1.3375	15.0	15000	1.4164	1.0	402.5571	10.3995
1.303	16.0	16000	1.4152	1.0	401.2788	10.4281
1.2215	17.0	17000	1.4149	1.0	400.1707	10.5308
1.2239	18.0	18000	1.4094	1.0	399.5269	10.6309
1.1587	19.0	19000	1.4067	1.0	399.8632	10.6802
1.1162	20.0	20000	1.4118	1.0	401.0874	10.7793
1.0873	21.0	21000	1.4137	1.0	401.0856	10.8705
1.0534	22.0	22000	1.4207	1.0	397.3273	10.8864
1.0039	23.0	23000	1.4275	1.0	401.2085	10.9394

Framework versions

Transformers 4.57.0
Pytorch 2.8.0+cu128
Datasets 4.2.0
Tokenizers 0.22.1

contemmcm/a0b648d6e0c2065718b942c275329ea8

a0b648d6e0c2065718b942c275329ea8

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

contemmcm/
a0b648d6e0c2065718b942c275329ea8