tsavage68_-_mpt_1000_STEPS_1e6_rate_05_beta_DPO-8bits – AI Model by RichardErkhov | AlphaNeural AI

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tsavage68_-_mpt_1000_STEPS_1e6_rate_05_beta_DPO-8bits

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mpt_1000_STEPS_1e6_rate_05_beta_DPO - bnb 8bits

Model creator: https://huggingface.co/tsavage68/
Original model: https://huggingface.co/tsavage68/mpt_1000_STEPS_1e6_rate_05_beta_DPO/

Original model description:

license: apache-2.0 base_model: mosaicml/mpt-7b-instruct tags:

trl
dpo
generated_from_trainer model-index:
name: mpt_1000_STEPS_1e8_rate_03_beta_DPO results: []

mpt_1000_STEPS_1e8_rate_03_beta_DPO

This model is a fine-tuned version of mosaicml/mpt-7b-instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6941
Rewards/chosen: -1.2875
Rewards/rejected: -1.6132
Rewards/accuracies: 0.6154
Rewards/margins: 0.3257
Logps/rejected: -24.7839
Logps/chosen: -23.3672
Logits/rejected: 14.1648
Logits/chosen: 14.1681

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: 1e-06
train_batch_size: 2
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.7473	0.1	100	0.6927	0.1811	0.1159	0.5582	0.0651	-21.3256	-20.4301	14.3166	14.3195
0.7098	0.2	200	0.7624	0.6571	0.5345	0.5714	0.1226	-20.4884	-19.4780	14.1537	14.1566
0.7516	0.29	300	0.7505	-0.8487	-1.0927	0.5429	0.2440	-23.7428	-22.4895	14.5590	14.5620
0.7762	0.39	400	0.7476	-2.2343	-2.4798	0.5692	0.2455	-26.5171	-25.2608	14.0064	14.0094
0.8328	0.49	500	0.7228	-1.5283	-1.7877	0.5736	0.2594	-25.1329	-23.8488	14.1811	14.1843
0.625	0.59	600	0.7006	-1.3183	-1.6353	0.5978	0.3170	-24.8281	-23.4288	14.3453	14.3486
0.7164	0.68	700	0.7015	-1.2944	-1.6029	0.6022	0.3084	-24.7632	-23.3811	14.2239	14.2271
0.6844	0.78	800	0.6985	-1.2758	-1.5914	0.6198	0.3157	-24.7403	-23.3437	14.1630	14.1663
0.6996	0.88	900	0.6971	-1.2896	-1.6092	0.6110	0.3196	-24.7758	-23.3713	14.1673	14.1706
0.6352	0.98	1000	0.6941	-1.2875	-1.6132	0.6154	0.3257	-24.7839	-23.3672	14.1648	14.1681

Framework versions

Transformers 4.39.1
Pytorch 2.0.0+cu117
Datasets 2.18.0
Tokenizers 0.15.2