falcon-7b-ft-self_instruct

mrm8488/falcon-7b-ft-self_instruct

falcon-7b-ft-self_instruct is a machine learning model from mrm8488. 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 Jun 24, 2023

Repo size

533 MB

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Public

Hugging Face

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At a glance

Access: Public
Created: Jun 23, 2023
Updated: Jun 24, 2023
SHA: 49aecdb1

Model card

From the Hugging Face model README

falcon-7b-ft-self_instruct

This model is a fine-tuned version of ybelkada/falcon-7b-sharded-bf16 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7991

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: 0.0002
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.03
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.9935	0.09	100	1.0028
1.0094	0.17	200	0.9614
0.8897	0.26	300	0.9396
0.9435	0.34	400	0.9260
0.9618	0.43	500	0.9146
0.8103	0.52	600	0.9035
0.8889	0.6	700	0.8966
0.8915	0.69	800	0.8884
0.8814	0.77	900	0.8833
0.9207	0.86	1000	0.8742
0.8284	0.95	1100	0.8693
0.8283	1.03	1200	0.8682
0.7445	1.12	1300	0.8659
0.8238	1.2	1400	0.8640
0.7448	1.29	1500	0.8537
0.7866	1.38	1600	0.8534
0.7224	1.46	1700	0.8480
0.7235	1.55	1800	0.8399
0.7936	1.64	1900	0.8385
0.7487	1.72	2000	0.8337
0.7842	1.81	2100	0.8284
0.7198	1.89	2200	0.8251
0.7507	1.98	2300	0.8188
0.622	2.07	2400	0.8353
0.6592	2.15	2500	0.8358
0.6043	2.24	2600	0.8330
0.7259	2.32	2700	0.8324
0.6388	2.41	2800	0.8290
0.7284	2.5	2900	0.8224
0.6166	2.58	3000	0.8202
0.6132	2.67	3100	0.8122
0.6323	2.75	3200	0.8094
0.6686	2.84	3300	0.8034
0.6457	2.93	3400	0.7991

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Created: Jun 23, 2023
Updated: Jun 24, 2023