phi-2-hummanize1

This model is a fine-tuned version of microsoft/phi-2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 6.7074

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: 0.0025
• train_batch_size: 20
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 20
• total_train_batch_size: 400
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 2
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.02	1	2.0864
No log	0.05	2	4.0671
No log	0.07	3	3.6332
No log	0.09	4	2.5537
3.0197	0.11	5	2.3394
3.0197	0.14	6	2.8862
3.0197	0.16	7	2.5140
3.0197	0.18	8	2.4603
3.0197	0.21	9	2.2094
2.5958	0.23	10	2.1767
2.5958	0.25	11	2.3343
2.5958	0.28	12	2.2511
2.5958	0.3	13	2.1854
2.5958	0.32	14	2.1385
2.2944	0.34	15	2.3556
2.2944	0.37	16	2.2056
2.2944	0.39	17	2.2127
2.2944	0.41	18	2.1507
2.2944	0.44	19	2.1388
2.2841	0.46	20	2.6540
2.2841	0.48	21	2.8934
2.2841	0.51	22	3.0981
2.2841	0.53	23	2.4155
2.2841	0.55	24	2.1754
2.7585	0.57	25	2.0927
2.7585	0.6	26	2.0865
2.7585	0.62	27	2.2345
2.7585	0.64	28	2.4123
2.7585	0.67	29	2.7718
2.3906	0.69	30	4.2964
2.3906	0.71	31	6.5295
2.3906	0.73	32	5.8489
2.3906	0.76	33	7.2467
2.3906	0.78	34	7.6353
6.5839	0.8	35	7.7842
6.5839	0.83	36	8.8627
6.5839	0.85	37	7.9511
6.5839	0.87	38	9.7736
6.5839	0.9	39	8.3666
8.6795	0.92	40	8.9768
8.6795	0.94	41	9.0808
8.6795	0.96	42	8.5933
8.6795	0.99	43	8.9317
8.6795	1.01	44	8.5291
8.8177	1.03	45	8.5935
8.8177	1.06	46	8.6773
8.8177	1.08	47	8.5914
8.8177	1.1	48	8.5006
8.8177	1.13	49	8.3959
8.6883	1.15	50	8.2375
8.6883	1.17	51	8.2022
8.6883	1.19	52	8.2063
8.6883	1.22	53	8.2254
8.6883	1.24	54	8.3408
8.4216	1.26	55	8.0367
8.4216	1.29	56	7.8776
8.4216	1.31	57	7.6720
8.4216	1.33	58	7.5050
8.4216	1.35	59	7.3863
7.8151	1.38	60	7.3775
7.8151	1.4	61	7.3820
7.8151	1.42	62	7.2597
7.8151	1.45	63	7.1959
7.8151	1.47	64	7.1233
7.3639	1.49	65	7.0625
7.3639	1.52	66	7.0302
7.3639	1.54	67	6.9862
7.3639	1.56	68	6.9601
7.3639	1.58	69	6.9606
7.1152	1.61	70	6.8977
7.1152	1.63	71	6.8981
7.1152	1.65	72	6.8453
7.1152	1.68	73	6.8523
7.1152	1.7	74	6.8641
6.9712	1.72	75	6.8261
6.9712	1.75	76	6.8273
6.9712	1.77	77	6.8053
6.9712	1.79	78	6.7712
6.9712	1.81	79	6.7542
6.8925	1.84	80	6.7466
6.8925	1.86	81	6.7341
6.8925	1.88	82	6.7255
6.8925	1.91	83	6.7211
6.8925	1.93	84	6.7154
6.8192	1.95	85	6.7103
6.8192	1.97	86	6.7074

Framework versions

• PEFT 0.8.2
• Transformers 4.38.0.dev0
• Pytorch 2.1.0+cu118
• Datasets 2.17.0
• Tokenizers 0.15.2