results

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: 0.7266

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: 4
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.8268	0.08	1000	0.7354
0.7977	0.16	2000	0.7251
0.7739	0.24	3000	0.7259
0.771	0.32	4000	0.7269
0.7468	0.4	5000	0.7269
0.751	0.48	6000	0.7501
0.7483	0.56	7000	0.7502
0.7443	0.64	8000	0.7253
0.7294	0.72	9000	0.7309
0.7309	0.8	10000	0.7260
0.7424	0.88	11000	0.7304
0.7348	0.96	12000	0.7276
0.7421	1.04	13000	0.7327
0.7333	1.12	14000	0.7417
0.7444	1.2	15000	0.7296
0.7463	1.28	16000	0.7257
0.7324	1.3600	17000	0.7253
0.7297	1.44	18000	0.7314
0.7358	1.52	19000	0.7253
0.7442	1.6	20000	0.7248
0.7384	1.6800	21000	0.7388
0.7345	1.76	22000	0.7259
0.7218	1.8400	23000	0.7284
0.7426	1.92	24000	0.7253
0.7375	2.0	25000	0.7389
0.7443	2.08	26000	0.7305
0.7286	2.16	27000	0.7258
0.7269	2.24	28000	0.7264
0.7391	2.32	29000	0.7270
0.7377	2.4	30000	0.7283
0.7319	2.48	31000	0.7329
0.7352	2.56	32000	0.7254
0.7141	2.64	33000	0.7285
0.7317	2.7200	34000	0.7253
0.7334	2.8	35000	0.7305
0.7332	2.88	36000	0.7282
0.7309	2.96	37000	0.7266

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0
• Datasets 3.0.0
• Tokenizers 0.19.1