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RichardErkhov/
marcchew_-_TinyLLaMA-1.1B-OrcaPlatty-gguf

Name: marcchew_-_TinyLLaMA-1.1B-OrcaPlatty-gguf
Availability: InStock

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Quantization made by Richard Erkhov.

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TinyLLaMA-1.1B-OrcaPlatty - GGUF

Model creator: https://huggingface.co/marcchew/
Original model: https://huggingface.co/marcchew/TinyLLaMA-1.1B-OrcaPlatty/

Name	Quant method	Size
TinyLLaMA-1.1B-OrcaPlatty.Q2_K.gguf	Q2_K	0.4GB
TinyLLaMA-1.1B-OrcaPlatty.IQ3_XS.gguf	IQ3_XS	0.44GB
TinyLLaMA-1.1B-OrcaPlatty.IQ3_S.gguf	IQ3_S	0.47GB
TinyLLaMA-1.1B-OrcaPlatty.Q3_K_S.gguf	Q3_K_S	0.47GB
TinyLLaMA-1.1B-OrcaPlatty.IQ3_M.gguf	IQ3_M	0.48GB
TinyLLaMA-1.1B-OrcaPlatty.Q3_K.gguf	Q3_K	0.51GB
TinyLLaMA-1.1B-OrcaPlatty.Q3_K_M.gguf	Q3_K_M	0.51GB
TinyLLaMA-1.1B-OrcaPlatty.Q3_K_L.gguf	Q3_K_L	0.55GB
TinyLLaMA-1.1B-OrcaPlatty.IQ4_XS.gguf	IQ4_XS	0.57GB
TinyLLaMA-1.1B-OrcaPlatty.Q4_0.gguf	Q4_0	0.59GB
TinyLLaMA-1.1B-OrcaPlatty.IQ4_NL.gguf	IQ4_NL	0.6GB
TinyLLaMA-1.1B-OrcaPlatty.Q4_K_S.gguf	Q4_K_S	0.6GB
TinyLLaMA-1.1B-OrcaPlatty.Q4_K.gguf	Q4_K	0.62GB
TinyLLaMA-1.1B-OrcaPlatty.Q4_K_M.gguf	Q4_K_M	0.62GB
TinyLLaMA-1.1B-OrcaPlatty.Q4_1.gguf	Q4_1	0.65GB
TinyLLaMA-1.1B-OrcaPlatty.Q5_0.gguf	Q5_0	0.71GB
TinyLLaMA-1.1B-OrcaPlatty.Q5_K_S.gguf	Q5_K_S	0.71GB
TinyLLaMA-1.1B-OrcaPlatty.Q5_K.gguf	Q5_K	0.73GB
TinyLLaMA-1.1B-OrcaPlatty.Q5_K_M.gguf	Q5_K_M	0.73GB
TinyLLaMA-1.1B-OrcaPlatty.Q5_1.gguf	Q5_1	0.77GB
TinyLLaMA-1.1B-OrcaPlatty.Q6_K.gguf	Q6_K	0.84GB
TinyLLaMA-1.1B-OrcaPlatty.Q8_0.gguf	Q8_0	1.09GB

Original model description:

license: apache-2.0 base_model: jeff31415/TinyLlama-1.1B-1T-OpenOrca tags:

generated_from_trainer model-index:
name: results results: []

results

This model is a fine-tuned version of jeff31415/TinyLlama-1.1B-1T-OpenOrca on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.5156

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: 9e-07
train_batch_size: 20
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 80
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
2.1726	0.03	8	2.3170
2.1444	0.05	16	2.2937
2.1036	0.08	24	2.2707
2.0703	0.1	32	2.2478
2.0604	0.13	40	2.2248
2.046	0.15	48	2.2013
1.9919	0.18	56	2.1780
1.9842	0.21	64	2.1547
1.9234	0.23	72	2.1320
1.9235	0.26	80	2.1099
1.9096	0.28	88	2.0884
1.8722	0.31	96	2.0679
1.8594	0.34	104	2.0479
1.8438	0.36	112	2.0283
1.7581	0.39	120	2.0089
1.7852	0.41	128	1.9901
1.7634	0.44	136	1.9714
1.7296	0.46	144	1.9531
1.6976	0.49	152	1.9353
1.6861	0.52	160	1.9173
1.6683	0.54	168	1.8993
1.6255	0.57	176	1.8826
1.619	0.59	184	1.8673
1.6455	0.62	192	1.8534
1.5784	0.65	200	1.8399
1.6078	0.67	208	1.8259
1.5703	0.7	216	1.8124
1.5215	0.72	224	1.7989
1.542	0.75	232	1.7852
1.5147	0.77	240	1.7721
1.5092	0.8	248	1.7589
1.4564	0.83	256	1.7456
1.4985	0.85	264	1.7324
1.4505	0.88	272	1.7189
1.4447	0.9	280	1.7052
1.4436	0.93	288	1.6924
1.4132	0.95	296	1.6799
1.3791	0.98	304	1.6680
1.3877	1.01	312	1.6565
1.3807	1.03	320	1.6453
1.3391	1.06	328	1.6352
1.3232	1.08	336	1.6251
1.3293	1.11	344	1.6159
1.3029	1.14	352	1.6074
1.3173	1.16	360	1.5992
1.3006	1.19	368	1.5926
1.2547	1.21	376	1.5863
1.2704	1.24	384	1.5805
1.2964	1.26	392	1.5749
1.277	1.29	400	1.5695
1.2718	1.32	408	1.5657
1.2379	1.34	416	1.5619
1.2746	1.37	424	1.5585
1.2349	1.39	432	1.5559
1.2264	1.42	440	1.5531
1.2365	1.45	448	1.5505
1.2242	1.47	456	1.5484
1.2094	1.5	464	1.5462
1.2196	1.52	472	1.5444
1.2447	1.55	480	1.5426
1.2127	1.57	488	1.5407
1.2278	1.6	496	1.5391
1.2089	1.63	504	1.5377
1.2069	1.65	512	1.5361
1.2264	1.68	520	1.5350
1.2027	1.7	528	1.5338
1.2138	1.73	536	1.5325
1.207	1.75	544	1.5313
1.2155	1.78	552	1.5304
1.2192	1.81	560	1.5295
1.2223	1.83	568	1.5287
1.2281	1.86	576	1.5278
1.1977	1.88	584	1.5269
1.2101	1.91	592	1.5261
1.2099	1.94	600	1.5254
1.1873	1.96	608	1.5245
1.204	1.99	616	1.5242
1.21	2.01	624	1.5239
1.242	2.04	632	1.5231
1.1696	2.06	640	1.5224
1.1803	2.09	648	1.5218
1.1692	2.12	656	1.5213
1.212	2.14	664	1.5208
1.1977	2.17	672	1.5204
1.187	2.19	680	1.5201
1.1858	2.22	688	1.5199
1.1824	2.25	696	1.5194
1.1914	2.27	704	1.5190
1.1815	2.3	712	1.5187
1.2021	2.32	720	1.5184
1.1872	2.35	728	1.5181
1.1901	2.37	736	1.5178
1.1933	2.4	744	1.5177
1.1773	2.43	752	1.5175
1.1935	2.45	760	1.5172
1.2118	2.48	768	1.5170
1.1816	2.5	776	1.5169
1.1842	2.53	784	1.5167
1.1891	2.55	792	1.5165
1.1883	2.58	800	1.5164
1.1506	2.61	808	1.5163
1.1708	2.63	816	1.5162
1.1944	2.66	824	1.5160
1.1575	2.68	832	1.5159
1.1698	2.71	840	1.5160
1.1525	2.74	848	1.5158
1.1767	2.76	856	1.5157
1.1943	2.79	864	1.5158
1.1727	2.81	872	1.5157
1.195	2.84	880	1.5157
1.1771	2.86	888	1.5157
1.1731	2.89	896	1.5156
1.191	2.92	904	1.5157
1.1903	2.94	912	1.5156
1.1821	2.97	920	1.5156
1.2	2.99	928	1.5156

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.15.1.dev0
Tokenizers 0.15.0

RichardErkhov/marcchew_-_TinyLLaMA-1.1B-OrcaPlatty-gguf

Original model description:

results

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
marcchew_-_TinyLLaMA-1.1B-OrcaPlatty-gguf