opus-mt-ar-en-finetunedTanzil-v6-ar-to-en

This model is a fine-tuned version of Helsinki-NLP/opus-mt-ar-en on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.6863
• Validation Loss: 0.8789
• Train Rouge1: 56.4999
• Train Rouge2: 33.3152
• Train Rougel: 52.7922
• Train Rougelsum: 53.4004
• Train Gen Len: 65.66
• Epoch: 14

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:

• optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Rouge1	Train Rouge2	Train Rougel	Train Rougelsum	Train Gen Len	Epoch
1.2958	1.2191	55.4125	33.4250	52.1444	52.4427	109.29	0
1.1928	1.1607	57.1190	35.0261	53.9195	54.3028	103.37	1
1.1152	1.1133	56.7848	34.9767	53.6885	54.0708	81.705	2
1.0531	1.0795	56.5101	35.1214	53.2131	53.4955	104.285	3
0.9999	1.0493	57.7130	35.7997	54.7519	55.0195	98.01	4
0.9544	1.0233	57.4034	35.3118	54.2593	54.6092	56.94	5
0.9135	1.0009	56.7008	35.3027	53.6876	53.8885	94.855	6
0.8770	0.9793	56.6660	34.4890	53.1461	53.5412	93.33	7
0.8434	0.9624	55.3198	33.4441	52.3099	52.7027	94.63	8
0.8135	0.9468	55.2723	33.4791	51.9936	52.2751	69.765	9
0.7842	0.9335	55.9241	33.1444	52.5591	52.8279	63.895	10
0.7572	0.9170	57.7109	34.8199	54.0893	54.6004	75.57	11
0.7322	0.9009	55.7067	33.2829	52.2642	52.5643	96.515	12
0.7084	0.8912	55.2352	32.1104	51.6885	52.1647	91.595	13
0.6863	0.8789	56.4999	33.3152	52.7922	53.4004	65.66	14

Framework versions

• Transformers 4.17.0.dev0
• TensorFlow 2.7.0
• Datasets 1.18.4.dev0
• Tokenizers 0.10.3