llamantino7b_2_15_question-answering

This model is a fine-tuned version of swap-uniba/LLaMAntino-2-7b-hf-ITA on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.9020
• Rouge1: 20.66
• Rouge2: 12.6
• Rougel: 19.61
• Rougelsum: 19.59
• R: 17.6
• Gen Len: 1.0
• R@1: 0.0
• R@3: 0.0
• R@5: 0.0
• R@10: 0.0
• R@20: 0.0

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: 0.0002
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.03
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	R	Gen Len	R@1	R@3	R@5	R@10	R@20
1.7673	1.0	23	1.4057	17.21	6.55	15.45	16.11	13.04	1.0	0.0	0.0	0.0	0.0	0.0
1.1784	2.0	46	1.2798	19.12	9.4	17.55	17.74	15.33	1.0	0.0	0.0	0.0	0.0	0.0
0.69	3.0	69	1.3161	20.11	11.2	18.93	18.99	16.72	1.0	0.0	0.0	0.0	0.0	0.0
0.3671	4.0	92	1.3626	20.22	11.39	19.09	19.02	16.87	1.0	0.0	0.0	0.0	0.0	0.0
0.1942	5.0	115	1.4936	20.63	12.07	19.27	19.35	17.3	1.0	0.0	0.0	0.0	0.0	0.0
0.1074	6.0	138	1.5033	21.36	12.63	20.11	20.12	18.01	1.0	0.0	0.0	0.0	0.0	0.0
0.0617	7.0	161	1.6100	21.13	12.29	19.81	19.86	17.72	1.0	0.0	0.0	0.0	0.0	0.0
0.0462	8.0	184	1.6695	20.91	12.48	19.74	19.66	17.69	1.0	0.0	0.0	0.0	0.0	0.0
0.0328	9.0	207	1.6829	21.33	12.66	20.08	20.19	18.0	1.0	0.0	0.0	0.0	0.0	0.0
0.0239	10.0	230	1.7029	20.82	12.48	19.59	19.58	17.61	1.0	0.0	0.0	0.0	0.0	0.0
0.015	11.0	253	1.7664	20.62	12.44	19.42	19.49	17.47	1.0	0.0	0.0	0.0	0.0	0.0
0.0104	12.0	276	1.8431	20.72	12.64	19.58	19.6	17.62	1.0	0.0	0.0	0.0	0.0	0.0
0.0085	13.0	299	1.8640	20.63	12.62	19.57	19.53	17.58	1.0	0.0	0.0	0.0	0.0	0.0
0.0073	14.0	322	1.8931	20.6	12.64	19.6	19.57	17.59	1.0	0.0	0.0	0.0	0.0	0.0
0.006	15.0	345	1.9020	20.66	12.6	19.61	19.59	17.6	1.0	0.0	0.0	0.0	0.0	0.0

Framework versions

• PEFT 0.8.2
• Transformers 4.38.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.16.1
• Tokenizers 0.15.2