Training Loss	Epoch	Step	Validation Loss
1.1766	0.01	68	1.2007
1.0903	0.02	136	1.1284
1.0809	0.03	204	1.0993
1.0928	0.04	272	1.0712
0.989	0.05	340	1.0473
1.0044	0.06	408	1.0373
0.985	0.07	476	1.0241
1.0272	0.08	544	1.0130
1.0295	0.09	612	1.0036
1.0172	0.1	680	0.9985
0.9582	0.11	748	0.9924
1.0342	0.12	816	0.9916
1.0053	0.13	884	0.9844
0.9321	0.14	952	0.9798
0.9473	0.15	1020	0.9727
0.9197	0.16	1088	0.9688
0.9827	0.17	1156	0.9632
0.9423	0.18	1224	0.9613
0.9662	0.19	1292	0.9578
0.9417	0.2	1360	0.9549
0.9501	0.21	1428	0.9461
0.9744	0.22	1496	0.9466
0.8693	0.23	1564	0.9394
0.9467	0.24	1632	0.9393
0.9274	0.25	1700	0.9362
0.8793	0.26	1768	0.9338
0.99	0.27	1836	0.9276
0.8983	0.28	1904	0.9291
0.9177	0.29	1972	0.9246
0.9586	0.3	2040	0.9224
0.9364	0.31	2108	0.9178
0.9248	0.32	2176	0.9175
0.9294	0.33	2244	0.9171
0.9142	0.34	2312	0.9136
0.9533	0.35	2380	0.9102
0.9193	0.36	2448	0.9094
0.9072	0.37	2516	0.9075
0.8927	0.38	2584	0.9043
0.9055	0.39	2652	0.9032
0.9276	0.4	2720	0.9030
0.8847	0.41	2788	0.8966
0.9449	0.42	2856	0.8963
0.8754	0.43	2924	0.8971
0.8612	0.44	2992	0.8935
0.9028	0.45	3060	0.8895
0.8641	0.46	3128	0.8925
0.8668	0.47	3196	0.8887
0.8935	0.48	3264	0.8863
0.8889	0.49	3332	0.8837
0.8854	0.5	3400	0.8849
0.8725	0.51	3468	0.8831
0.9425	0.52	3536	0.8796
0.8577	0.53	3604	0.8780
0.8281	0.54	3672	0.8747
0.9141	0.55	3740	0.8736
0.8684	0.56	3808	0.8738
0.8476	0.57	3876	0.8718
0.8761	0.58	3944	0.8735
0.8464	0.59	4012	0.8708
0.8732	0.6	4080	0.8681
0.9441	0.61	4148	0.8669
0.881	0.62	4216	0.8657
0.8635	0.63	4284	0.8640
0.827	0.64	4352	0.8625
0.9123	0.65	4420	0.8628
0.8557	0.66	4488	0.8605
0.8157	0.67	4556	0.8591
0.9008	0.68	4624	0.8580
0.8574	0.69	4692	0.8580
0.8374	0.7	4760	0.8563
0.8698	0.71	4828	0.8554
0.8817	0.72	4896	0.8545
0.8375	0.73	4964	0.8532
0.8504	0.74	5032	0.8524
0.8526	0.75	5100	0.8516
0.9306	0.76	5168	0.8511
0.7999	0.77	5236	0.8502
0.8337	0.78	5304	0.8495
0.7934	0.79	5372	0.8488
0.8159	0.8	5440	0.8480
0.7997	0.81	5508	0.8473
0.8909	0.82	5576	0.8470
0.852	0.83	5644	0.8461
0.8285	0.84	5712	0.8455
0.8437	0.85	5780	0.8448
0.8784	0.86	5848	0.8444
0.8123	0.87	5916	0.8440
0.8439	0.88	5984	0.8436
0.8847	0.89	6052	0.8433
0.8165	0.9	6120	0.8429
0.8405	0.91	6188	0.8427
0.8641	0.92	6256	0.8425
0.8536	0.93	6324	0.8424
0.8426	0.94	6392	0.8421
0.8547	0.95	6460	0.8421
0.8144	0.96	6528	0.8419
0.8475	0.97	6596	0.8419
0.8063	0.98	6664	0.8419
0.7943	0.99	6732	0.8419

Framework versions

Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2

mlabonne/grandpythia-200k-70m

grandpythia-200k-70m

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mlabonne/
grandpythia-200k-70m