meeting-sensai

This model is a fine-tuned version of raquelclemente/tmp_trainer on the None dataset. It achieves the following results on the evaluation set:

• Loss: 6.7917
• Rouge1: 0.4205
• Rouge2: 0.1795
• Rougel: 0.3536
• Rougelsum: 0.3536

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: 0.0005
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 5
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
No log	2.46	5	3.6391	0.4237	0.1996	0.3660	0.3660
No log	4.91	10	3.4021	0.4118	0.2142	0.3778	0.3778
No log	7.46	15	3.5879	0.4314	0.2218	0.3965	0.3965
No log	9.91	20	3.8672	0.4730	0.2043	0.4003	0.4003
No log	12.46	25	3.8721	0.4083	0.1885	0.3675	0.3675
No log	14.91	30	4.0905	0.4609	0.2105	0.4070	0.4070
No log	17.46	35	4.4786	0.4580	0.1856	0.3739	0.3739
No log	19.91	40	4.9112	0.4689	0.2573	0.4224	0.4224
No log	22.46	45	5.2165	0.4698	0.2151	0.4096	0.4096
No log	24.91	50	5.5533	0.4014	0.1837	0.3062	0.3062
No log	27.46	55	5.8611	0.4109	0.1854	0.3686	0.3686
No log	29.91	60	5.8393	0.4715	0.2370	0.4074	0.4074
No log	32.46	65	6.1874	0.4297	0.1898	0.3479	0.3479
No log	34.91	70	6.3194	0.4350	0.2207	0.3802	0.3802
No log	37.46	75	6.2460	0.4009	0.2056	0.3518	0.3518
No log	39.91	80	6.5997	0.3992	0.1869	0.3713	0.3713
No log	42.46	85	6.5516	0.4345	0.1928	0.3756	0.3756
No log	44.91	90	6.5791	0.4078	0.2036	0.3489	0.3489
No log	47.46	95	6.7799	0.4205	0.1795	0.3536	0.3536
No log	49.91	100	6.7917	0.4205	0.1795	0.3536	0.3536

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.0
• Datasets 2.1.0
• Tokenizers 0.13.2