V0422MADP6A

Litzy619/V0422MADP6A

V0422MADP6A is a machine learning model from Litzy619. Use it for the machine learning task on the model card, and read the license before you ship it in a product.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

Access

Public

Updated Apr 22, 2024

Parameters

2.9B

6.5 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors5.9 GB · 91%

Parameter types

How the weights are stored.

F162.8B · 97%

Base models

microsoft/phi-2

Model card

From the Hugging Face model README

V0422MADP6A

This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1488

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
gradient_accumulation_steps: 16
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine_with_restarts
lr_scheduler_warmup_steps: 60
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
8.4055	0.09	10	2.9936
5.8544	0.18	20	2.3868
2.0051	0.27	30	0.9445
0.3844	0.36	40	0.2819
0.1879	0.45	50	0.1972
0.1698	0.54	60	0.1618
0.1606	0.63	70	0.1677
0.1587	0.73	80	0.1580
0.1514	0.82	90	0.1483
0.15	0.91	100	0.1509
0.155	1.0	110	0.1488
0.1505	1.09	120	0.1518
0.1561	1.18	130	0.1542
0.1504	1.27	140	0.1540
0.1536	1.36	150	0.1510
0.1532	1.45	160	0.1522
0.1551	1.54	170	0.1551
0.1531	1.63	180	0.1476
0.1553	1.72	190	0.1612
0.1541	1.81	200	0.1500
0.1587	1.9	210	0.1573
0.1554	1.99	220	0.1592
0.1592	2.08	230	0.1645
0.1499	2.18	240	0.1542
0.149	2.27	250	0.1550
0.1516	2.36	260	0.1547
0.1504	2.45	270	0.1500
0.1466	2.54	280	0.1510
0.1476	2.63	290	0.1501
0.1468	2.72	300	0.1489
0.1464	2.81	310	0.1489
0.1486	2.9	320	0.1488
0.1498	2.99	330	0.1488

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.14.1

Created: Apr 22, 2024
Updated: Apr 22, 2024