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lukaspetersson/
tinyllama-addition-refuse

Name: tinyllama-addition-refuse
Availability: InStock

generated_from_trainer

generator

unsloth/tinyllama-chat-bnb-4bit

adapter

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outputs

This model is a fine-tuned version of unsloth/tinyllama-chat-bnb-4bit on the generator dataset. It achieves the following results on the evaluation set:

Loss: 0.4551

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: 2e-05
train_batch_size: 2
eval_batch_size: 2
seed: 3407
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.9638	0.0	1	1.9504
1.9792	0.0	2	1.9467
1.9213	0.0	3	1.9308
2.0225	0.0	4	1.8936
1.8364	0.0	5	1.8278
1.7729	0.0	6	1.7366
1.9591	0.01	7	1.6324
1.6693	0.01	8	1.5278
1.6387	0.01	9	1.4367
1.5681	0.01	10	1.3741
1.3459	0.01	11	1.3300
1.311	0.01	12	1.2931
1.2721	0.01	13	1.2534
1.353	0.01	14	1.2140
1.1664	0.01	15	1.1727
1.27	0.01	16	1.1344
1.1007	0.01	17	1.0966
1.1035	0.01	18	1.0608
1.0744	0.01	19	1.0278
1.0491	0.02	20	0.9973
1.0057	0.02	21	0.9688
0.9435	0.02	22	0.9423
0.9612	0.02	23	0.9169
0.9811	0.02	24	0.8932
0.9263	0.02	25	0.8700
0.8581	0.02	26	0.8468
0.8351	0.02	27	0.8237
0.8019	0.02	28	0.8008
0.8526	0.02	29	0.7786
0.773	0.02	30	0.7571
0.7436	0.02	31	0.7365
0.7455	0.03	32	0.7172
0.747	0.03	33	0.6995
0.727	0.03	34	0.6834
0.6859	0.03	35	0.6687
0.6642	0.03	36	0.6552
0.6715	0.03	37	0.6428
0.6538	0.03	38	0.6311
0.5947	0.03	39	0.6202
0.6537	0.03	40	0.6102
0.601	0.03	41	0.6008
0.5956	0.03	42	0.5921
0.5875	0.03	43	0.5842
0.5737	0.03	44	0.5769
0.5618	0.04	45	0.5701
0.546	0.04	46	0.5638
0.5908	0.04	47	0.5578
0.6172	0.04	48	0.5520
0.5652	0.04	49	0.5467
0.5357	0.04	50	0.5417
0.5524	0.04	51	0.5370
0.5352	0.04	52	0.5326
0.5356	0.04	53	0.5283
0.518	0.04	54	0.5242
0.5273	0.04	55	0.5201
0.5099	0.04	56	0.5161
0.5158	0.04	57	0.5123
0.521	0.05	58	0.5084
0.5177	0.05	59	0.5047
0.4964	0.05	60	0.5010
0.502	0.05	61	0.4974
0.5078	0.05	62	0.4942
0.4814	0.05	63	0.4913
0.4863	0.05	64	0.4887
0.4998	0.05	65	0.4864
0.5106	0.05	66	0.4842
0.5273	0.05	67	0.4822
0.4874	0.05	68	0.4803
0.4697	0.05	69	0.4785
0.4796	0.05	70	0.4768
0.4767	0.06	71	0.4753
0.4582	0.06	72	0.4739
0.5084	0.06	73	0.4725
0.4566	0.06	74	0.4712
0.4583	0.06	75	0.4700
0.4753	0.06	76	0.4689
0.4528	0.06	77	0.4678
0.4617	0.06	78	0.4667
0.499	0.06	79	0.4656
0.4368	0.06	80	0.4646
0.4939	0.06	81	0.4637
0.4446	0.06	82	0.4627
0.4428	0.07	83	0.4618
0.4737	0.07	84	0.4611
0.4391	0.07	85	0.4603
0.4985	0.07	86	0.4597
0.45	0.07	87	0.4590
0.4642	0.07	88	0.4585
0.4633	0.07	89	0.4579
0.4233	0.07	90	0.4574
0.4478	0.07	91	0.4570
0.4768	0.07	92	0.4565
0.4665	0.07	93	0.4562
0.4504	0.07	94	0.4560
0.4692	0.07	95	0.4557
0.4326	0.08	96	0.4555
0.4727	0.08	97	0.4554
0.4658	0.08	98	0.4553
0.4905	0.08	99	0.4552
0.4501	0.08	100	0.4551

Framework versions

PEFT 0.8.2
Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2

lukaspetersson/tinyllama-addition-refuse

outputs

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lukaspetersson/
tinyllama-addition-refuse