pegasusx-AMI-text-summarizer

This model is a fine-tuned version of google/pegasus-x-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.9024

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: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 35

Training results

Training Loss	Epoch	Step	Validation Loss
4.6836	0.77	10	4.2972
4.6013	1.53	20	4.1099
4.5902	2.3	30	3.9257
4.3479	3.06	40	3.8087
4.1995	3.83	50	3.6779
4.0121	4.59	60	3.5480
3.8925	5.36	70	3.4199
3.7548	6.12	80	3.2936
3.4644	6.89	90	3.1752
3.2484	7.66	100	3.0529
3.2456	8.42	110	2.9345
3.2281	9.19	120	2.8282
2.9944	9.95	130	2.7188
2.8439	10.72	140	2.6208
2.8192	11.48	150	2.5434
2.631	12.25	160	2.4852
2.5715	13.01	170	2.4277
2.5404	13.78	180	2.3876
2.4297	14.55	190	2.3507
2.4243	15.31	200	2.3110
2.4517	16.08	210	2.2733
2.3127	16.84	220	2.2454
2.3058	17.61	230	2.2127
2.1694	18.37	240	2.1808
2.1908	19.14	250	2.1532
2.1474	19.9	260	2.1234
2.1264	20.67	270	2.1139
2.0156	21.44	280	2.0933
2.0264	22.2	290	2.0611
2.0338	22.97	300	2.0448
2.055	23.73	310	2.0302
1.7735	24.5	320	2.0117
1.8999	25.26	330	2.0005
1.8606	26.03	340	1.9795
1.7847	26.79	350	1.9744
1.7478	27.56	360	1.9614
1.8806	28.33	370	1.9514
1.6817	29.09	380	1.9436
1.689	29.86	390	1.9351
1.649	30.62	400	1.9292
1.715	31.39	410	1.9181
1.5847	32.15	420	1.9077
1.6016	32.92	430	1.9112
1.532	33.68	440	1.9018
1.4849	34.45	450	1.9024

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.0
• Tokenizers 0.15.2