fine-tune-bart

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

• Loss: 0.8951
• Rouge1: 0.3436
• Rouge2: 0.1406
• Rougel: 0.3117
• Rougelsum: 0.3108
• Gen Len: 15.43

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	301	0.7910	0.2441	0.0841	0.2149	0.2154	14.55
1.8181	2.0	602	0.7323	0.256	0.0926	0.2294	0.2291	13.25
1.8181	3.0	903	0.7217	0.2794	0.1079	0.2491	0.2465	14.48
0.6902	4.0	1204	0.7233	0.3095	0.1209	0.2782	0.277	14.38
0.5826	5.0	1505	0.7241	0.2985	0.1239	0.2628	0.2633	14.68
0.5826	6.0	1806	0.7184	0.3312	0.1309	0.2968	0.2978	15.53
0.4967	7.0	2107	0.7332	0.3127	0.1324	0.2856	0.2857	14.86
0.4967	8.0	2408	0.7419	0.3379	0.1391	0.3027	0.3035	14.7
0.429	9.0	2709	0.7580	0.3473	0.1417	0.318	0.3178	14.65
0.3799	10.0	3010	0.7505	0.338	0.1406	0.3057	0.3033	15.18
0.3799	11.0	3311	0.7783	0.3444	0.1341	0.3139	0.3126	15.12
0.341	12.0	3612	0.7893	0.3231	0.1294	0.2991	0.2993	14.97
0.341	13.0	3913	0.7957	0.347	0.1376	0.3105	0.3101	15.3
0.299	14.0	4214	0.8134	0.3275	0.1367	0.3023	0.3012	14.84
0.263	15.0	4515	0.8191	0.3125	0.1364	0.2873	0.2875	15.17
0.263	16.0	4816	0.8196	0.3276	0.1334	0.3011	0.2996	15.32
0.2394	17.0	5117	0.8389	0.3168	0.1244	0.2856	0.2881	15.07
0.2394	18.0	5418	0.8502	0.3398	0.1328	0.3123	0.3112	15.06
0.2157	19.0	5719	0.8584	0.3257	0.1197	0.2937	0.2936	15.36
0.1957	20.0	6020	0.8633	0.3325	0.1295	0.2986	0.2994	15.4
0.1957	21.0	6321	0.8620	0.3254	0.1208	0.2952	0.2949	15.28
0.181	22.0	6622	0.8762	0.3395	0.1306	0.3054	0.3045	15.27
0.181	23.0	6923	0.8775	0.3419	0.14	0.3137	0.3126	15.24
0.1622	24.0	7224	0.8780	0.3397	0.1311	0.3069	0.3063	15.15
0.1613	25.0	7525	0.8859	0.3231	0.1225	0.2887	0.288	15.14
0.1613	26.0	7826	0.8905	0.3289	0.1284	0.2953	0.2941	15.23
0.1463	27.0	8127	0.8883	0.3358	0.1303	0.3002	0.2988	15.19
0.1463	28.0	8428	0.8933	0.3414	0.139	0.3113	0.3098	15.5
0.1444	29.0	8729	0.8949	0.3449	0.1369	0.311	0.31	15.43
0.135	30.0	9030	0.8951	0.3436	0.1406	0.3117	0.3108	15.43

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0