metadata

license: apache-2.0
base_model: facebook/bart-large
tags:
  - generated_from_trainer
metrics:
  - rouge
  - wer
model-index:
  - name: bart_baseline_1024
    results: []

bart_baseline_1024

This model is a fine-tuned version of facebook/bart-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.9558
Rouge1: 0.7069
Rouge2: 0.4544
Rougel: 0.6489
Rougelsum: 0.6489
Wer: 0.4398

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: 6
eval_batch_size: 6
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Wer
No log	0.13	250	1.2224	0.665	0.3911	0.6	0.6001	0.4993
2.0905	0.27	500	1.1190	0.6743	0.4083	0.6103	0.6104	0.4809
2.0905	0.4	750	1.0832	0.6818	0.418	0.6178	0.6178	0.4726
1.188	0.53	1000	1.0541	0.6871	0.4246	0.6242	0.6242	0.4675
1.188	0.66	1250	1.0352	0.6881	0.4283	0.6269	0.6268	0.4628
1.1172	0.8	1500	1.0291	0.6912	0.4319	0.6303	0.6303	0.4586
1.1172	0.93	1750	1.0079	0.7001	0.4406	0.6396	0.6397	0.4543
1.0803	1.06	2000	0.9957	0.6939	0.4396	0.6359	0.6359	0.4511
1.0803	1.2	2250	0.9891	0.6972	0.443	0.6383	0.6383	0.4479
0.9849	1.33	2500	0.9800	0.7009	0.4467	0.6425	0.6425	0.4464
0.9849	1.46	2750	0.9771	0.7017	0.4479	0.6426	0.6426	0.4437
0.9867	1.6	3000	0.9638	0.7085	0.4541	0.6495	0.6495	0.4422
0.9867	1.73	3250	0.9675	0.7013	0.4495	0.6438	0.6438	0.4413
0.9556	1.86	3500	0.9565	0.707	0.4544	0.6493	0.6492	0.4401
0.9556	1.99	3750	0.9558	0.7069	0.4544	0.6489	0.6489	0.4398

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2