test

This model is a fine-tuned version of Uzair54/test on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0057
• Gen Len: 19.0
• P: 0.6886
• R: 0.0017
• F1: 0.3237
• Bleu-score: 6.6728
• Bleu-precisions: [94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]
• Bleu-bp: 0.0708

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: 0.0003
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Gen Len	P	R	F1	Bleu-score	Bleu-precisions	Bleu-bp
No log	1.0	25	0.0251	19.0	0.6885	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	2.0	50	0.0466	19.0	0.6885	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	3.0	75	0.0277	19.0	0.6889	0.0016	0.3238	6.6660	[94.99185667752442, 94.56233421750663, 94.05222437137331, 93.43649946638207]	0.0707
No log	4.0	100	0.0188	19.0	0.6885	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	5.0	125	0.0164	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	6.0	150	0.0150	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	7.0	175	0.0140	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	8.0	200	0.0128	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	9.0	225	0.0110	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	10.0	250	0.0111	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	11.0	275	0.0095	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	12.0	300	0.0086	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	13.0	325	0.0081	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	14.0	350	0.0074	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	15.0	375	0.0070	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	16.0	400	0.0066	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	17.0	425	0.0062	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	18.0	450	0.0059	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
No log	19.0	475	0.0058	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708
0.0237	20.0	500	0.0057	19.0	0.6886	0.0017	0.3237	6.6728	[94.95319495319495, 94.52054794520548, 94.00676655389077, 93.38666666666667]	0.0708

Framework versions

• Transformers 4.39.3
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2