README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - un_multi
metrics:
  - bleu
model-index:
  - name: opus-mt-en-ar-finetuned-en-to-ar
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: un_multi
          type: un_multi
          args: ar-en
        metrics:
          - name: Bleu
            type: bleu
            value: 64.6767

opus-mt-en-ar-finetuned-en-to-ar

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

• Loss: 0.8133
• Bleu: 64.6767
• Gen Len: 17.595

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: 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: 16
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
No log	1.0	50	0.7710	64.3416	17.4
No log	2.0	100	0.7569	63.9546	17.465
No log	3.0	150	0.7570	64.7484	17.385
No log	4.0	200	0.7579	65.4073	17.305
No log	5.0	250	0.7624	64.8939	17.325
No log	6.0	300	0.7696	65.1257	17.45
No log	7.0	350	0.7747	65.527	17.395
No log	8.0	400	0.7791	65.1357	17.52
No log	9.0	450	0.7900	65.3812	17.415
0.3982	10.0	500	0.7925	65.7346	17.39
0.3982	11.0	550	0.7951	65.1267	17.62
0.3982	12.0	600	0.8040	64.6874	17.495
0.3982	13.0	650	0.8069	64.7788	17.52
0.3982	14.0	700	0.8105	64.6701	17.585
0.3982	15.0	750	0.8120	64.7111	17.58
0.3982	16.0	800	0.8133	64.6767	17.595

Framework versions

• Transformers 4.19.2
• Pytorch 1.11.0+cu113
• Datasets 2.2.2
• Tokenizers 0.12.1