nllb-200-distilled-600M-finetuned_ramayana_sns_prose

This model is a fine-tuned version of facebook/nllb-200-distilled-600M on the None dataset. It achieves the following results on the evaluation set:

• Loss: 3.5584
• Rouge1: 19.8304
• Rouge2: 2.4248
• Rougel: 13.9446
• Rougelsum: 18.3552

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-06
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
4.595	1.0	427	4.1428	15.776	1.4778	12.3256	14.3476
4.1875	2.0	854	3.9597	16.6403	1.7896	12.7134	15.0805
4.0304	3.0	1281	3.8653	16.6812	1.8152	12.5282	15.1217
3.9243	4.0	1708	3.7984	17.1533	1.788	13.1478	15.5023
3.8485	5.0	2135	3.7505	17.3886	1.8682	13.1805	15.711
3.786	6.0	2562	3.7141	17.7897	1.9953	13.2044	15.9314
3.732	7.0	2989	3.6815	18.3797	2.0735	13.8603	16.7243
3.6865	8.0	3416	3.6559	18.2702	2.0286	13.3494	16.5957
3.6515	9.0	3843	3.6354	18.0194	1.9282	12.9295	16.4714
3.6177	10.0	4270	3.6193	18.7825	2.0085	13.2207	17.1223
3.5877	11.0	4697	3.6030	19.1192	2.1276	13.9442	17.609
3.5665	12.0	5124	3.5943	19.5031	2.3146	13.7631	17.9879
3.5454	13.0	5551	3.5828	19.7688	2.2574	13.9943	18.2914
3.5247	14.0	5978	3.5763	19.4478	2.3024	13.8854	17.9616
3.509	15.0	6405	3.5704	19.3998	2.2633	13.707	17.9534
3.4983	16.0	6832	3.5646	19.6401	2.3265	13.9141	18.2001
3.4865	17.0	7259	3.5604	19.1833	2.398	13.6566	17.7596
3.4802	18.0	7686	3.5584	19.8304	2.4248	13.9446	18.3552

Framework versions

• Transformers 4.41.2
• Pytorch 2.0.1+cu117
• Datasets 2.19.2
• Tokenizers 0.19.1