distillation_objective: DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl, layer_mapper=None, projector=None), hs_loss_component=LossComponent(label=hs, weight=2.0, loss_fn=mse, layer_mapper=None, projector=None), attn_loss_component=LossComponent(label=attn, weight=0, loss_fn=None, layer_mapper=None, projector=None))
train_embeddings: True
learning_rate: 4e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 1.0

Resource Usage

Peak GPU Memory: 8.0873 GB

Eval-Phase Metrics

step	epoch	enwikippl	frwikippl	loss	runtime	samples_per_second	steps_per_second	zhwikippl
teacher eval		30.2086	57.2728					18.1784
0	0	56314.7695	59887.2773	5.8256	85.6711	58.363	7.295	59033.8086
1000	0.0162	703.3142	4236.9004	1.8490	85.6638	58.368	7.296	11133.5088
2000	0.0323	504.8312	3192.5520	1.6764	85.4461	58.516	7.315	1842.1659
3000	0.0485	421.6048	2827.9453	1.5711	85.6065	58.407	7.301	841.4271
4000	0.0646	359.8385	2300.7822	1.4898	85.5248	58.463	7.308	1321.4115
5000	0.0808	320.1989	1782.2493	1.4134	85.6041	58.408	7.301	921.9020
6000	0.0970	279.3613	1572.2640	1.3457	85.4507	58.513	7.314	775.6033
7000	0.1131	252.3406	1452.0632	1.2901	85.4137	58.539	7.317	675.1237
8000	0.1293	230.5502	1345.9784	1.2423	85.9632	58.164	7.271	594.2899
9000	0.1455	215.5059	1193.6056	1.2009	85.3591	58.576	7.322	627.1483
10000	0.1616	194.5708	1147.0729	1.1501	85.2878	58.625	7.328	681.0092
11000	0.1778	179.9636	1066.1221	1.1062	85.2181	58.673	7.334	556.0541
12000	0.1939	165.4222	900.6642	1.0627	85.2275	58.667	7.333	517.4376
13000	0.2101	155.7605	880.5709	1.0328	85.4983	58.481	7.31	504.9460
14000	0.2263	148.5429	820.9711	1.0057	85.4522	58.512	7.314	432.5430
15000	0.2424	142.2881	752.3494	0.9840	85.291	58.623	7.328	371.8599
16000	0.2586	138.4622	756.4453	0.9709	85.5234	58.464	7.308	645.2426
17000	0.2747	136.4131	709.4854	0.9606	85.2257	58.668	7.333	653.3060
18000	0.2909	133.8840	722.0003	0.9493	85.2137	58.676	7.335	538.2999
19000	0.3071	131.9743	726.1355	0.9435	85.2513	58.65	7.331	595.8792
20000	0.3232	129.7892	706.8889	0.9335	85.2873	58.625	7.328	420.4131
21000	0.3394	127.3829	659.1836	0.9238	85.0899	58.761	7.345	377.2113
22000	0.3556	125.8100	627.8823	0.9149	85.107	58.75	7.344	378.1191
23000	0.3717	124.3241	675.1288	0.9101	85.2843	58.627	7.328	407.0987
24000	0.3879	121.7446	648.3518	0.9012	85.2715	58.636	7.33	370.7195
25000	0.4040	121.8676	673.0380	0.8998	85.4414	58.52	7.315	401.9131
26000	0.4202	121.1881	598.3207	0.8906	85.1925	58.691	7.336	455.3015
27000	0.4364	119.8778	614.9578	0.8859	85.3813	58.561	7.32	291.9007
28000	0.4525	119.7104	589.9427	0.8831	85.3094	58.61	7.326	313.4760
29000	0.4687	118.6553	652.7549	0.8794	85.2629	58.642	7.33	299.0819
30000	0.4848	118.7475	602.5115	0.8775	85.4036	58.546	7.318	355.6388
31000	0.5010	118.1863	610.4652	0.8759	85.1743	58.703	7.338	275.1334
32000	0.5172	117.4726	628.6798	0.8750	85.2859	58.626	7.328	301.3671
33000	0.5333	115.1694	602.0021	0.8713	85.2629	58.642	7.33	277.0137
34000	0.5495	115.8600	574.1846	0.8689	85.1695	58.706	7.338	277.8658
35000	0.5657	114.0391	537.2504	0.8629	85.3032	58.614	7.327	307.7109
36000	0.5818	115.1694	602.9366	0.8660	85.3327	58.594	7.324	328.2996
37000	0.5980	113.9152	575.0357	0.8590	85.7449	58.313	7.289	332.3134
38000	0.6141	114.4739	573.7802	0.8618	85.7064	58.339	7.292	270.8683
39000	0.6303	112.6310	546.8427	0.8543	85.2884	58.625	7.328	289.1075
40000	0.6465	112.8762	570.1909	0.8537	85.2282	58.666	7.333	257.7758
41000	0.6626	112.9112	548.9287	0.8543	85.3272	58.598	7.325	325.8972
42000	0.6788	111.7424	549.7032	0.8534	85.5416	58.451	7.306	291.7448
43000	0.6949	112.2556	568.9060	0.8524	85.2667	58.64	7.33	310.9328
44000	0.7111	110.7490	603.5746	0.8525	85.3547	58.579	7.322	269.4612
45000	0.7273	112.0378	593.0288	0.8486	85.4267	58.53	7.316	378.8268
46000	0.7434	111.5950	589.0699	0.8492	85.0567	58.784	7.348	364.7776
47000	0.7596	112.7010	588.7380	0.8558	85.186	58.695	7.337	446.9284
48000	0.7758	114.3584	519.3724	0.8590	85.1156	58.744	7.343	2148.5159
49000	0.7919	115.1962	590.7754	0.8648	85.1589	58.714	7.339	430.9863
50000	0.8081	114.1809	614.9578	0.8597	85.2319	58.663	7.333	309.8965
51000	0.8242	112.0117	593.5725	0.8551	85.2128	58.677	7.335	423.6820
52000	0.8404	109.5515	563.6358	0.8457	85.2439	58.655	7.332	337.9521
53000	0.8566	109.7388	550.0908	0.8446	85.1744	58.703	7.338	412.3510
54000	0.8727	111.3959	551.1781	0.8453	85.2832	58.628	7.329	368.3508
55000	0.8889	111.1712	575.0760	0.8450	85.1663	58.709	7.339	283.8286
56000	0.9051	110.6545	557.3918	0.8454	85.4688	58.501	7.313	360.2272
57000	0.9212	110.4055	604.0854	0.8479	85.3777	58.563	7.32	420.6379
58000	0.9374	111.5257	635.6327	0.8466	85.6212	58.397	7.3	492.8218
59000	0.9535	109.2372	581.6412	0.8423	85.6034	58.409	7.301	366.9761
60000	0.9697	108.7379	565.1876	0.8362	85.2814	58.629	7.329	331.8257
61000	0.9859	108.9746	583.4484	0.8370	85.1729	58.704	7.338	399.4518
61875	1.0	109.4665	569.9899	0.8351	85.5074	58.474	7.309	290.9278

Framework versions

Distily 0.2.0
Transformers 4.44.0
Pytorch 2.3.0
Datasets 2.21.0

lapp0/distily_bench_gpt2_activation_loss_c

distily_bench_gpt2_activation_loss_c

Training procedure

Training hyperparameters

Resource Usage

Eval-Phase Metrics

Framework versions

lapp0/
distily_bench_gpt2_activation_loss_c