BramVanroy/mbart-large-cc25-ft-amr30-nl

nl+no_processing

This model is a fine-tuned version of facebook/mbart-large-cc25 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6038
• Smatch Precision: 73.7
• Smatch Recall: 76.48
• Smatch Fscore: 75.06
• Smatch Unparsable: 0
• Percent Not Recoverable: 0.2323

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: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Smatch Precision	Smatch Recall	Smatch Fscore	Smatch Unparsable	Percent Not Recoverable
0.8025	1.0	3477	1.3793	18.51	65.71	28.88	0	0.0
0.13	2.0	6954	0.9377	27.0	71.3	39.16	0	0.1161
0.0953	3.0	10431	0.7509	34.09	72.74	46.42	0	0.1161
0.1386	4.0	13908	0.8524	33.38	73.32	45.87	2	0.0
0.0974	5.0	17385	0.6957	41.69	73.92	53.31	0	0.0
0.0705	6.0	20862	0.6145	47.98	75.12	58.55	0	0.0
0.2265	7.0	24339	0.6439	47.06	75.53	57.99	0	0.0
0.0506	8.0	27817	0.5974	53.0	76.95	62.77	0	0.0
0.064	9.0	31294	0.6387	51.83	77.47	62.11	0	0.0
0.0112	10.0	34771	0.6066	54.82	76.98	64.03	0	0.0
0.047	11.0	38248	0.5970	60.36	77.04	67.69	0	0.0
0.0134	12.0	41725	0.5675	61.72	77.15	68.58	0	0.0
0.0656	13.0	45202	0.6210	62.8	76.92	69.15	0	0.0581
0.015	14.0	48679	0.6257	62.8	77.32	69.31	0	0.0
0.0134	15.0	52156	0.5635	66.7	77.34	71.63	0	0.1161
0.0265	16.0	55634	0.5839	67.61	76.76	71.89	0	0.0581
0.0219	17.0	59111	0.5894	68.66	77.43	72.78	0	0.1161
0.0008	18.0	62588	0.5981	68.44	77.57	72.72	0	0.0
0.0157	19.0	66065	0.6184	69.88	77.42	73.46	0	0.0581
0.0334	20.0	69542	0.6026	70.76	77.37	73.92	0	0.2323
0.0619	21.0	73019	0.6021	72.03	77.0	74.44	0	0.1742
0.0075	22.0	76496	0.6166	72.33	76.74	74.47	0	0.0581
0.0164	23.0	79973	0.6100	72.75	77.03	74.83	0	0.2323
0.0011	24.0	83451	0.6037	73.7	76.51	75.08	0	0.2323
0.0865	25.0	86925	0.6038	73.7	76.48	75.06	0	0.2323

Framework versions

• Transformers 4.34.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.14.2
• Tokenizers 0.13.3