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Acadys/
PointCon-Mixtral

Name: PointCon-Mixtral
Rating: 2.5 (6 reviews)

peft

safetensors

generated_from_trainer

mistralai/Mixtral-8x7B-Instruct-v0.1

adapter

apache-2.0

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Mixtral-8x7B-Instruct-v0.1

This model is a fine-tuned version of mistralai/Mixtral-8x7B-Instruct-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.3898

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: 5e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.8837	0.01	5	1.7824
1.8578	0.02	10	1.7336
1.6828	0.02	15	1.6999
1.8063	0.03	20	1.6716
1.6728	0.04	25	1.6400
1.5326	0.05	30	1.6079
1.5742	0.05	35	1.5795
1.6315	0.06	40	1.5597
1.6111	0.07	45	1.5449
1.5815	0.08	50	1.5359
1.4937	0.09	55	1.5234
1.4524	0.09	60	1.5177
1.4922	0.1	65	1.5150
1.5636	0.11	70	1.5058
1.5303	0.12	75	1.5020
1.4182	0.12	80	1.5003
1.4375	0.13	85	1.4919
1.4287	0.14	90	1.4873
1.5023	0.15	95	1.4859
1.5331	0.16	100	1.4800
1.4797	0.16	105	1.4784
1.476	0.17	110	1.4741
1.5398	0.18	115	1.4702
1.4086	0.19	120	1.4670
1.4222	0.19	125	1.4648
1.4033	0.2	130	1.4623
1.5386	0.21	135	1.4608
1.4959	0.22	140	1.4583
1.4908	0.22	145	1.4542
1.4669	0.23	150	1.4510
1.4733	0.24	155	1.4477
1.5692	0.25	160	1.4458
1.484	0.26	165	1.4468
1.4186	0.26	170	1.4432
1.3907	0.27	175	1.4391
1.4489	0.28	180	1.4392
1.471	0.29	185	1.4364
1.31	0.29	190	1.4344
1.3949	0.3	195	1.4324
1.4094	0.31	200	1.4306
1.4235	0.32	205	1.4275
1.5056	0.33	210	1.4271
1.4281	0.33	215	1.4251
1.4329	0.34	220	1.4236
1.3791	0.35	225	1.4221
1.4189	0.36	230	1.4207
1.4192	0.36	235	1.4198
1.3807	0.37	240	1.4187
1.4362	0.38	245	1.4177
1.419	0.39	250	1.4174
1.5039	0.4	255	1.4176
1.4323	0.4	260	1.4160
1.5249	0.41	265	1.4154
1.4462	0.42	270	1.4144
1.2841	0.43	275	1.4137
1.3764	0.43	280	1.4137
1.3063	0.44	285	1.4123
1.4296	0.45	290	1.4122
1.4333	0.46	295	1.4110
1.3113	0.47	300	1.4103
1.3138	0.47	305	1.4103
1.3951	0.48	310	1.4104
1.3592	0.49	315	1.4099
1.458	0.5	320	1.4094
1.4037	0.5	325	1.4094
1.4431	0.51	330	1.4086
1.3595	0.52	335	1.4076
1.3198	0.53	340	1.4061
1.3967	0.53	345	1.4054
1.254	0.54	350	1.4049
1.3324	0.55	355	1.4047
1.2428	0.56	360	1.4037
1.3976	0.57	365	1.4033
1.4226	0.57	370	1.4036
1.3678	0.58	375	1.4038
1.4634	0.59	380	1.4028
1.4325	0.6	385	1.4018
1.3175	0.6	390	1.4013
1.3263	0.61	395	1.4007
1.3653	0.62	400	1.4019
1.3804	0.63	405	1.4009
1.3686	0.64	410	1.4003
1.3975	0.64	415	1.4003
1.3289	0.65	420	1.4000
1.3336	0.66	425	1.3991
1.3958	0.67	430	1.3979
1.2227	0.67	435	1.3972
1.3202	0.68	440	1.3967
1.3508	0.69	445	1.3963
1.4077	0.7	450	1.3956
1.4148	0.71	455	1.3952
1.4219	0.71	460	1.3948
1.3802	0.72	465	1.3949
1.301	0.73	470	1.3945
1.2894	0.74	475	1.3938
1.3469	0.74	480	1.3940
1.2852	0.75	485	1.3941
1.4896	0.76	490	1.3933
1.3953	0.77	495	1.3929
1.3624	0.78	500	1.3926
1.4719	0.78	505	1.3927
1.3274	0.79	510	1.3920
1.2106	0.8	515	1.3917
1.3851	0.81	520	1.3918
1.344	0.81	525	1.3916
1.3197	0.82	530	1.3917
1.3426	0.83	535	1.3922
1.266	0.84	540	1.3919
1.392	0.84	545	1.3918
1.325	0.85	550	1.3918
1.4706	0.86	555	1.3915
1.3695	0.87	560	1.3910
1.4036	0.88	565	1.3912
1.3042	0.88	570	1.3912
1.2578	0.89	575	1.3912
1.3579	0.9	580	1.3915
1.3324	0.91	585	1.3913
1.5166	0.91	590	1.3911
1.3563	0.92	595	1.3907
1.4271	0.93	600	1.3901
1.4084	0.94	605	1.3899
1.3975	0.95	610	1.3897
1.3887	0.95	615	1.3896
1.4221	0.96	620	1.3898
1.4031	0.97	625	1.3898
1.3114	0.98	630	1.3897
1.4907	0.98	635	1.3896
1.3519	0.99	640	1.3898
1.3648	1.0	645	1.3898

Framework versions

PEFT 0.7.1
Transformers 4.36.2
Pytorch 2.1.0+cu118
Datasets 2.16.1
Tokenizers 0.15.0

Acadys/PointCon-Mixtral

Mixtral-8x7B-Instruct-v0.1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Acadys/
PointCon-Mixtral